470
bdttpdblend
We will utilize the Open Science Grid to conduct quantum chemical calculations and kinetic Monte Carlo simulations of organic photovoltaic morphologies. We have a simulation pipeline that enables high throughput material screening for chemistires and processing conditions relevent for organic photovoltaic devices. We will use molecular configurations from previously simulated morphologies, generated with molecular dynamics code accelerated by GPUs.
Eric Jankowski
Boise State University
Material Science and Engineering
Computational Condensed Matter Physics
14
OSG Connect
658
UWMadison_McMillan
Understanding structure of neural networks
Alan McMillan
University of Wisconsin-Madison
Radiology
Medical Imaging
14
OSG Connect
632
UCSD_ResearchIT
General group for OSG testing and prototyping
Alan Moxley
University of California, San Diego
Information Technology
Other
14
OSG Connect
747
TexasAM_Sun
Light nuclei production in heavy-ion collisions
Kaijia Sun
Texas A&M University
Cyclotron Institute
Physics
14
OSG Connect
37035824
Illinois_2022_Tsokaros
Research includes general and numerical relativity, astrophysics, cosmology, and alternative theories of gravity.
Antonios Tsokaros
University of Illinois Urbana-Champaign
Physics
Astrophysics
21
PATh Facility
1635310641
BrighamAndWomens_Baratono
Studying how atrophy and connectivity to atrophy impacts cognitive and psychological outcomes in patients with a variety of neurodegenerative disorders
Sheena R Baratono
Brigham and Women's Hospital
Neurology
Biological and Biomedical Sciences
234
cms.org.cmu
CMS Connect at Carnegie-Mellon University
Manfred Paulini
Carnegie-Mellon University
Physics
High Energy Physics
18
CMS Connect
536
CatalystDesign
Catalyst design project with a heterogenous catalyst, looking for stable structures
Dequan Xiao
University of New Haven
Chemistry and Chemical Engineering
Chemistry
14
OSG Connect
165
TG-AST150033
The Kepler Mission has detected dozens of compact planetary systems with more than four transiting planets. This sample provides a collection of close-packed planetary systems with relatively little spread in the inclination angles of the inferred orbits. A large fraction of the observational sample contains limited multiplicity, begging the question whether there is a true diversity of multi-transiting systems, or if some systems merely possess high mutual inclinations, allowing them to appear as single-transiting systems in a transit-based survey. Planet formation is an active yet poorly understood field: insight to the histories and dynamics of multi-planet systems would be helpful towards understanding planet formation as a whole.
In previous work, we have determined the regimes of parameter space for which orbital inclinations can be effectively excited by planet-planet interactions among the currently observed bodies. We found that the orbital inclination angles are not spread out appreciably through self-excitation. In contrast, we found that the two Kepler multi-planet systems with additional non-transiting planets are susceptible to oscillations of their inclination angles, which means their currently observed configurations could be due to planet-planet interactions alone. The multi-planet compact Kepler systems are found to be remarkably stable to oscillations of their inclination angles. The oscillations of inclination found in our previous work inform the recently suggested dichotomy in the sample of solar systems observed by Kepler. However, it would also be useful to study the behaviors of these systems with perturbing companions. This would enable a better understanding of the observed systems, resulting in a more accurate exoplanet population census. To do this, we must perform computationally intensive calculations and simulations.
Juliette Becker
University of Michigan
Astronomy
Astrophysics
13
OSG-XSEDE
818
UWMadison_DeLeon
Corn breeding and genetics
Natalia de Leon
University of Wisconsin-Madison
Agronomy
Agricultural Sciences
14
OSG Connect
1252207184
UCSD_Du
Our research group focuses on developing quantum sensing and imaging techniques to study various properties (spin, charge, and heat, etc) of quantum materials in the nanometer scale. In addition, we design and engineer hybrid quantum devices to achieve efficient qubit control for quantum information applications. Our research tools are versatile, including optical measurement based on nitrogen vacancy center in diamond, transport and microwave spectroscopy as well as scanning probe magnetometry.
Chunhui Du
University of California, San Diego
Physics
Physics
794
Workshop-RMACC21
Project for RMACC 2021 participants
Christina Koch
Open Science Grid
OSGConnect
Training
14
OSG Connect
723
Northeastern_RC
NU RC serves the university’s entire research community and helps facilitate access to HPC resources either on premise or in the cloud.
Raphael Schroter
Northeastern University
Information Technology Services - Research Computing
Computer Science
14
OSG Connect
628
UCLA_Zhu
Vision, Cognition, Learning and Autonomy
Song-Chun Zhu
University of California, Los Angeles
Computer Science
Computer Science
14
OSG Connect
1545725009
TG-TRA210040
I will be using the allocation to help researchers at the University of Rochester to understand how to use XSEDE resources and to test which XSEDE resources best fit their needs.
Baowei Liu
University of Rochester
Dept. of Physics & Astronomy
Training
14
OSG Connect
561
TG-CHE190012
Numerical demonstration of chiral molecule separation using circularly polarized light in an achiral environment under mild condition
Shengli Zou
University of Central Florida
Chemistry
Chemistry
13
OSG-XSEDE
764
PSU_Staff
Research computing staff at Penn State
Carrie Brown
Pennsylvania State University
Information Technology
Computer Sciences
14
OSG Connect
728
UNL_Fuchs
X-ray generation and characterization via Laser Wakefield Acceleration
Matthias Fuchs
University of Nebraska-Lincoln
Physics and Astronomy
Physics
14
OSG Connect
625
ASU_Pfeifer
Computational Genomics and Evolution
Susanne Pfeifer
Arizona State University
School of Life Sciences
Life Sciences - Biological and Biomedical
14
OSG Connect
370
lftsim
We are simulating quantum field theory and many particle systems using lattice field theory techniques. Although some of our work involves lattice QCD, much of it does not. It encompasses supersymmetric systems and phase transitions in nonrelativisting systems.
Joel Giedt
Rensselaer Polytechnic Institute
Physics
High Energy Physics
14
OSG Connect
718
Cornell_Pugh
Bioinformatics Tool Development
Frank Pugh
Cornell University
Molecular Biology and Genetics
Biological Sciences
14
OSG Connect
544
PixleyLab
Condensed matter theory including quantum phase transitions of many-body systems
Jedediah Pixley
Rutgers, The State University of New Jersey
Physics
Physics
14
OSG Connect
189
SciSim
The aim of this project is to create examples, demos and training materials to get UCF Faculty and Researchers get started for using OSG for HTC applications in the field of Scientific Simulations, Computation and Visualizations. Primarily, we expect to use NAMD, VMD, Matlab and R application software.
Amit Goel
University of Central Florida
Advanced Research Computing Center
Multi-Science Community
14
OSG Connect
13
sPHENIX
Collaboration devoted to simulation and design optimization of the prospected Super PHENIX detector (the successor of the existing PHENIX detector) at Relativistic Heavy Ion Collider (RHIC) at BNL.
Martin Purschke
Brookhaven National Laboratory
Physics Department
Nuclear Physics
30
OSG
817
UWMadison_Fredrickson
Intermetallic chemistry group interested in the origins of intergrowths
Daniel Fredrickson
University of Wisconsin-Madison
Chemistry
Chemistry
14
OSG Connect
996902537
BAERI_Bejaoui
Studying the photofragmentation of molecules excited with high energy photons
Salma Bejaoui
Bay Area Environmental Research Institute
Bay Area Environmental Research Institute
Astronomy & Astrophysics
14
OSG Connect
616
UCDenver_Mandel
regression testing on OSG
Jan Mandel
University of Colorado Denver
Mathematical and Statistical Sciences
Mathematics
14
OSG Connect
343
LiuLab
The project goal is to create new computational methodologies for large-scale phylogenomic analyses involving complex evolutionary histories.
Kevin Jensen Liu
Michigan State University
Computer Science and Engineering
Bioinformatics
14
OSG Connect
934335439
CSU_Buchanan
Modeling of magnetorheological elastomers
Kristen Buchanan
Colorado State University
Physics
Physics
168
MCP
We wish to use the Condor grid for running the program ARCIMBOLDO, which is geared for finding HT molecular replacement solutions. Because we have a recalcitrant system in our hands, we really need this system to solve our problem.
C. S. Raman
University of Maryland Baltimore
Pharmaceutical Sciences
Biochemistry
14
OSG Connect
495965557
UALR_EAC
The Donaghey Emerging Analytics Center (EAC, [http://eac.ualr.edu]) is an academic department within UA Little Rock with a focus on research and development in immersive visualization, augmented/virtual/mixed realities, and interactive technologies in general. The EAC is further including in its portfolio research in cybersecurity, mobile/ubiquitous computing, and the internet-of-things, as well as applications of machine and deep learning. Additionally, the EAC is collaborating very closely with the Department of Computer Science at UA Little Rock, where the computer science department is the prime talent pool for the EAC while the EAC offers wide-ranging opportunities for students in professional software development as well as academic and industry research.
Jan Springer
University of Arkansas at Little Rock
Donaghey Emerging Analytics Center
Computer and Information Science
14
OSG Connect
827
KSU_Ng
Structure-based drug discovery for cancer and immunology; computational structural biology and chemistry; protein photonics for imaging.
Ho Leung Ng
Kansas State University
Chemistry
Chemistry
14
OSG Connect
520
PorousMaterials
Calculating adsorption properties for porous materials using Monte Carlo algorithms or simulating Henry constants using Widom insertions. This is accomplished using a Julia code our group has developed, PorousMaterials.jl
Cory Simon
Oregon State University
Chemical, Biological and Environmental Engineering
Chemical Engineering
14
OSG Connect
821428041
SUNYUpstateMed_Schmitt
Studying the structure and phylogenetics of the ribonucleprotein complexes RNase MRP and P to apply to human and baker's yeast; Mining high-throughput and public datasets for information on the baker's yeast ribonucleoprotein complex RNase MRP' https://www.upstate.edu/biochem/research/fac_research.php?empID=schmittm
Mark Schmitt
SUNY Upstate Medical University
Department of Biochemistry & Molecular Biology
Biological and Biomedical Sciences
14
OSG Connect
2090385607
Arkansas_Nelson
Statistical analysis on keys generated by a lattice based cryptography algorithm for post-quantum cryptography to determine patterns in the types of errors produced in the keys.
Alexander Nelson
University of Arkansas
Computer Science & Computer Engineering
Computer Science
14
OSG Connect
2083162629
UPRM_Ramos
At present we are conducting molecular dynamics simulations to study the interaction of peptides and membranes. We are aiming at understanding the mechanisms (mechanical and/or electroestatic) that are involved in the formation of pores in membranes. In order to study these systems we are performing molecular dynamics simulations with NAMD and different force fields like charmm to simulate the formation of the pores.
Rafael A. Ramos
University of Puerto Rico - Mayaguez
Department of Physics
Physics
14
OSG Connect
742
JHU_Howard
The goal of this project is to support and expand analysis of open source data for computational mathematics, data science, and operations research.
James P. Howard, II
Johns Hopkins University
Mathematics
Mathematical Sciences
14
OSG Connect
169
TG-CCR140028
This allocation request is as the Rutgers Campus Champion to help serve the Rutgers Academic Community better.
Shantenu Jha
Rutgers, The State University of New Jersey
Computer Engineering
Computer and Information Science and Engineering
13
OSG-XSEDE
666
PortlandState_Feng
Vulnerable Ethereum Smart Contract Registry
Wu-chang Feng
Portland State University
Computer Sciences
Computer Science
14
OSG Connect
698705291
PSU_Anandakrishnan
Penn State Ice and Climate Exploration is an interdisciplinary group of researchers from across the university dedicated to a better understanding of the cryosphere.
Sridhar Anandakrishnan
Pennsylvania State University
Geosciences
Geological and Earth Sciences
14
OSG Connect
838
UNL_Stolle
MWRSF High Speed Computing
Cody Stolle
University of Nebraska - Lincoln
Mechanical & Materials Engineering
Engineering
14
OSG Connect
552
TG-TRA150015
Campus Champion for Wichita State University
Gi Suk Hwang
Wichita State University
Mechanical Engineering
Training
13
OSG-XSEDE
1448327643
Rochester_Franchini
The primary objective of this research project is to evaluate the efficacy and feasibility of an AI-powered pre-diagnostic tool for gastrointestinal diseases. Specifically, the project aims to assess the accuracy of the AI-powered technology in analyzing abdominal sounds and visual data recorded by the user's mobile phone.
Anthony Franchini
University of Rochester
University of Rochester Medical Centre
Biological and Biomedical Sciences
1808238491
ND_Colon
Looks into the use of transfer learning into the molecular framework space and application.
Yamil J. Colón
University of Notre Dame
Chemical Engineering
Chemical Engineering
14
OSG Connect
1377710926
KSU_Thumm
Theoretical studies on the time-resolved dissociative ionization of triatomic molecules (currently CO2) in ultrashort laser pulses
Uwe Thumm
Kansas State University
Department of Physics
Atomic Physics
14
OSG Connect
434
g4PSI
MUSE is an experiment to measure the proton radius using muon and electron scattering. I work on simulations of the experiment using GEANT4, a particle physics simulation toolkit.
Wolfgang Lorenzon
University of Michigan
Physics
High Energy Physics
14
OSG Connect
654
Flightworthy
HTCondor development activities
Miron Livny
University of Wisconsin-Madison
Computer Science
Computer Science
14
OSG Connect
1300616071
MiamiOH_Staff
Staff at Miami University in Ohio
Jens Mueller
Miami University
Research Office
Research Computing
14
OSG Connect
410
MCSpinLiquid
Perform monte carlo simulation on spin liquid systems
John McGreevy
University of California, San Diego
Physics
Physics
14
OSG Connect
39
TG-CHE130091
Compressed carbon dioxide is the main component of the mobile phase in supercritical fluid chromatography, which separates solutes according to their interactions with solid stationary phases. Molecular-scale properties of carbon dioxide in the mobile phase, confined near a stationary phase, and interacting with solutes can be calculated by Monte Carlo molecular simulation methods. Atomistic potentials for carbon dioxide, for solutes, and for the co-solvent methanol must be tested and refined to reliably simulate interactions at the pressure-temperature conditions of supercritical fluid chromatography. Simulation code now under development is well-suited to high-throughput computing in that it is serial, portable, and requires little RAM and disk storage. Because runs are long the code will be made check-pointable so simulations can efficiently use the Open Science Grid. The startup allocation requested will be to continue development of the serial simulation code, to modify it to allow restarting from a checkpoint file, then to test and improve atomistic potentials for solute and solvent molecules. It is against bulk fluid phase equilibrium data that potentials will be refined. Should service units remain after development work, computing will shift to characterizing the solvent within a few molecular diameters of stationary-phase and solute molecules.
Paul Siders
University of Minnesota Duluth
Chemistry and Biochemistry
Chemistry
13
OSG-XSEDE
442
MOLLER
The MOLLER experiment at Jefferson Lab is a Department of Energy supported project (currently past CD-0 status) that aims to determine the electroweak mixing angle to the highest precision at low energies through elastic electron-electron scattering.
Wouter Deconinck
Jefferson Lab
Physics
High Energy Physics
14
OSG Connect
598
clarkson_mondal
Feature Selection and Prediction of Rheumatoid Arthritis from Comorbidities using Bayesian Logistic Regression
Sumona Mondal
Clarkson University
Mathematics
Mathematics
14
OSG Connect
734
LANL_Chennupati
Training and examining machine learning models
Gopinath Chennupati
Los Alamos National Lab
Los Alamos National Laboratory
Computer Sciences
14
OSG Connect
749062086
FIU_Hamid
https://fphlm.cs.fiu.edu/
Shahid Hamid
Florida International University
IHRC
Ocean Sciences and Marine Sciences
14
OSG Connect
580
Hawaii_Doetinchem
This project intends to simulate the production of anti-helium-3 and anti-helium-4 in proton-proton collisions at different cosmic-ray energies. This is done by using the EPOS-LHC hadronic model and applying an energy-dependent coalescence afterburner.
Philip von Doetinchem
University of Hawaii at Manoa
Physics and Astronomy
Physics
14
OSG Connect
1146327518
Illinois_Jackson
Electronic Structure Model Using Coarse-Grained Representations
Nicholas Jackson
University of Illinois Urbana-Champaign
Chemistry
Chemistry
14
OSG Connect
2050048511
TCNJ_Science
Group for School of Science computing support/facilitators at The College of New Jersey
Sunita Kramer
The College of New Jersey
School of Science
Research Computing
14
OSG Connect
210
cms.org.purduecal
CMS Connect at Purdue University Calumet
Neeti Parashar
Purdue University Calumet
Physics
High Energy Physics
18
CMS Connect
91
atlas.org.duke
Duke University's Tier 2 ATLAS group in ATLAS Connect.
Doug Benjamin
Duke University
Physics
High Energy Physics
16
ATLAS Connect
262
atlas.org.nyu
ATLAS Connect team for New York University
Robert William Gardner Jr
New York University
Physics
High Energy Physics
16
ATLAS Connect
111
TG-TRA110013
Description: Campus Champions for Case Western Reserve University, helping faculty to start onboarding XSEDE resources. Some research work on Macromolecular Science and Materials Science.
Hadrian Djohari
Case Western Reserve University
ITS
Chemistry
13
OSG-XSEDE
446
BRDMS
This project is about simulation validation of a continuous data binning algorithm.
XUETONG ZHAI
University of Pittsburgh
Bioengineering
Biological Sciences
14
OSG Connect
235
cms.org.ohiostate
CMS connect at Ohio State University
Stan Durkin
Ohio State University
Physics
High Energy Physics
18
CMS Connect
7
Snowmass
Simulate hundreds of millions of high-energy
proton proton collisions, which mimic the
collisions expected at future hadron colliders.
This simulated data is used to assess the physics
potential of future colliders, allowing US
decision makers and funding agencies to prioritize
future physics projects.
Meenakshi Narain
Brown University
Physics
High Energy Physics
30
OSG
125
errorstudy
Missing data and genotyping errors are common features of microsatellite data sets used to infer the genetic structure of natural populations. We used simulated data to quantify the effect of these data aberrations on the accuracy of population structure inference. Data sets were simulated under the coalescent and ranged from panmictic to highly subdivided with complex, randomly generated, population histories. Models describing the characteristic patterns of missing data and genotyping error in real microsatellite data sets were developed, and used to modify the simulated data sets. Performance of an ordination, a tree based, and a model based Bayesian method of population structure inference was evaluated before and after data set modifications. The ability to recover correct population clusters decreased as missing data increased. The rate of decrease was similar among analytical procedures, thus no single analytical approach was preferable when
faced with incomplete data. Researchers should expect to retrieve 3–4% fewer correct clusters for every 1% of a data matrix made up of missing data using these methods. For every 1% of a matrix that contained erroneous genotypes, approximately 1–2% fewer correct clusters were recovered using ordination and tree based methods. A Bayesian procedure that minimizes the deviation from Hardy Weinberg equilibrium in order to assign individuals to clusters performed better as genotyping error increased. We attribute this surprising result to the inbreeding like nature of microsatellite genotyping error, and recommend the use of related analytical methods that explicitly account for inbreeding, as a means to mitigate the effect of genotyping error.
Christopher Richards
USDA Agricultural Research Service
National Center for Genetic Resources Preservation
Molecular and Structural Biosciences
14
OSG Connect
1272082860
UND_Delhommelle
Unraveling Crystallization and Phase Transition Processes through Topology, Rare-Event Simulations, and Machine Learning
Jerome Delhommelle
University of North Dakota
Chemistry
Physical Chemistry
14
OSG Connect
443747465
PSU_Kennea
Swift BAT data to localize Gamma-ray Bursts
Jamie Kennea
Pennsylvania State University
Department of Astronomy and Astrophysics
Astronomy
14
OSG Connect
430
WEST
Phenotyping leaf epidermis by optical tomography and computer vision to evaluate stomatal patterning across natural diversity and transgenic lines of Sorghum and Setaria
Dr. Andrew Leakey
University of Illinois Urbana-Champaign
Plant Biology
Plant Biology
14
OSG Connect
808
JLabMOLLER
Jefferson Lab's MOLLER experiment
Wouter Deconinck
Jefferson Lab
Physics
Nuclear Physics
99
JLab
454
cms.org.nd
CMS Connect at Notre Dame
Kevin Lannon
University of Notre Dame
High Energy Physics
Particle Physics
18
CMS Connect
1850803092
UWMadison_DeWerd
Simulations for radiation therapy applications
Larry DeWerd
University of Wisconsin-Madison
Medical Physics
Physics
358
HealthInformatics
My research focuses on detecting patterns in physiological data of patients in an Intensive Care Unit setting, with the aim of constructing an early warning system. The approach I am taking includes machine learning algorithms such as Artificial Neural Networks, Hidden Markov Models, and Support Vector Machines. I presently have limited computational resources for which to conduct this research. The data I am using for training and validation is both static and time based information on 32,000 patients and includes approximately 30GB of raw data. Additionally I have extremely high resolution data on 2,600 patient. The search-space is prohibitively large for a single computer and even some of the smaller clusters.
I am employing an optimization methodology which allows for a differential evolution approach to incrementally improve a structurally adaptive model. The methodology allows for parallel programming which is of course a necessity for distributed computing.
Karl Jablonowski
University of Washington
Biomedical and Health Informatics
Bioinformatics
14
OSG Connect
1422338289
Pitt_Aizenstein
We are applying novel machine learning methods to predict late life depression treatment response using neuroimaging data. We would utilize the computing resources to preprocess large amounts of neuroimaging data.
Howard Aizenstein
University of Pittsburgh
Department of Bioengineering
Biological and Biomedical Sciences
14
OSG Connect
356
VERITAS
VERITAS is an array of four imaging atmospheric Cherenkov telescopes to detect gamma-rays with energies above 100 GeV from astrophysical sources. This project produces Monte Carlo simulations of air showers and the detector response for VERITAS and other imaging Cherenkov telescope project
Nepomuk Otte
Georgia Institute of Technology
School of Physics & Center for Relativistic Astrophysics
Astrophysics
14
OSG Connect
527
nnmbl
I will be using techniques in machine learning and AI to better characterize the transition between the many-body localized and ergodic phases of the random field Heisenberg spin chain. Numerically, this will involve generating many disorder realizations of this model and calculating their spectra, and analyzing the resulting data using neural nets.
Ahmed Akhtar
University of California, San Diego
Physics
Computational Condensed Matter Physics
14
OSG Connect
1215969804
UMassLowell_Delhommelle
Unraveling Crystallization and Phase Transition Processes through Topology, Rare-Event Simulations, and Machine Learning
Jerome Delhommelle
University of Massachusetts Lowell
Chemistry
Physical Chemistry
14
OSG Connect
97
TG-CDA100013
Campus Champion renewal to support the University of North Carolina at Chapel Hill.
Mark Reed
University of North Carolina at Chapel Hill
ITS Research Computing
Mathematical Sciences
13
OSG-XSEDE
663
KSU_Staff
KSU Research Computing Staff
Dave Turner
Kansas State University
Computer Science
Advanced Scientific Computing
14
OSG Connect
177
FutureColliders
Studies of physics potential of future high-energy experiments
(VLHC, FCC) with performance significantly beyond the Large Hadron Collider. The project will focus on Monte Carlo simulations for future energy fronter at DOE
Sergei Chekanov
Argonne National Laboratory
High Energy Physics
High Energy Physics
14
OSG Connect
832
OSU_Weinberg
The project is about analyzing behaviors and primitives of market participants so that we can quantify effects coming from the changes in market competition, structure, policies, etc.
Matthew Weinberg
The Ohio State University
Economics
Economics
14
OSG Connect
517
swipnanobio
Run Pegasus workflows (parameter sweeps + data analysis) on our nanoBIO simulation code, looking for data integrity failures.
Von Welch
Indiana University
Center for Applied Cybersecurity Research
Neuroscience
14
OSG Connect
615
TG-AST190036
Exo-Cartography: Constraining Planet Formation through Mapping the Three-Dimensional Architectures of Planetary Systems
Juliette Becker
University of Michigan
Astronomy
Astronomical Sciences
13
OSG-XSEDE
374
all
The South Pole Telescope (or SPT) is a new telescope deployed at the South Pole that is designed to study the Cosmic Microwave background. Constructed between November 2006 and February 2007, the SPT is the largest telescope ever deployed at the South Pole. This telescope provides astronomers a powerful new tool to explore dark energy, the mysterious phenomena that may be causing the universe to accelerate. SPT members from various institutions are all added into this group. This group utilize the OSG opportunistic cycles.
John Carlstrom
University of Chicago
Physics
Astrophysics
19
SPT Connect
542
bobbot
DEM simulation for compression of active particles.
Daniel I Goldman
Georgia Institute of Technology
Physics
Biophysics
14
OSG Connect
414
BioAlgorithms
Algorithmic development for Bioinformatics
Natasha Pavlovikj
University of Nebraska-Lincoln
Computer Science
Bioinformatics
67
HCC
130
TG-CHE140098
The work proposed is Monte Carlo modeling of the interaction between mobile and sta-
tionary phases as they relate to supercritical fluid chromatography (SFC). Proposed research
continues that done with the startup allocation, which involved writing, testing, and porting
Monte Carlo code to model intermolecular interactions and fluid phase equilibria in com-
pressed carbon dioxide. Carbon dioxide is the main component of the mobile phase in SFC,
which typically operates at temperatures and and pressures above the critical point. The
objective of the proposed work is an understanding at the molecular level of the interac-
tion between mobile-phase molecules and the alkylsilane-coated silica stationary phase. The
computational method is Monte Carlo simulation, mainly in the constant-pressure Gibbs
ensemble. Hybrid molecular dynamics moves will be used for alklylsilane chains. Proposed
calculations will survey four alkylsilane coatings, eight pressures, three temperatures, and
three mobile-phase compositions. Compositions will be pure carbon dioxide and carbon
dioxide modified with 5% or 10% methanol. XSEDE resources requested are service units
on the Open Science Grid, which suits the small portable nature of the Monte Carlo code.
Weeks-long runs will be achieved by automatic resubmission of jobs.
Paul Siders
University of Minnesota Duluth
Chemistry and Biochemistry
Chemistry
13
OSG-XSEDE
473525047
AMNH_MacLow
Use an N-body code with analytic approximations to gas torques to model the formation of the hypothesized massive objects
Mordecai-Mark Mac Low
American Museum of Natural History
Astrophysics
Astronomy & Astrophysics
14
OSG Connect
638
LSMSA_Burkman
Solving optimization problems via genetic algorithms
John Bradford Burkman
Louisiana School for Math, Science, and the Arts
Math and Computer Science
Computer Sciences
14
OSG Connect
620
JLAB.EIC
Jefferson Lab's EIC project
Thomas Britton
Jefferson Lab
Physics
Nuclear Physics
99
JLab
337
TG-MCB160027
Knowledge of 3D protein structures is paramount towards our understanding of biochemistry. Currently, there are many more known protein sequences than 3D protein structures and experimentally determining their structure can be both expensive and time consuming. Therefore, extensive efforts have been made to model these structures using computational methods. Our group has developed the I-TASSER method, which constructs protein structure models by iteratively assembling structure fragments obtained by multiple threading algorithms. The method was stringently tested in the community-wide CASP experiments and has been widely used by the community, including more than 65,000 registered scientists from 122 countries. Despite its success, a major obstacle in the optimization of I-TASSER involves a dearth of computational resources available for use. We have access to a computing cluster composed of 1,100 cores. However, I-TASSER has seen a surge in users on our web server, and as a result, there have been over 2,000 jobs waiting or running at any one time, far exceeding our current capacity. Therefore, an increase in computational resources for our research interests would greatly benefit the further optimization of the I-TASSER method, as well as the biological and medical community as a whole. Over the course of this allocation, we expect to run approximately 400 I-TASSER jobs; each of these jobs would take 500 CPU hours, thus we would require roughly 200,000 CPU hours total. This will be of critical importance for the improvement of the I-TASSER methods and enhance its capacity to serve for the general biological community.
Yang Zhang
University of Michigan
Department of Computational Medicine and Bioinformatics
Molecular and Structural Biosciences
13
OSG-XSEDE
483473540
UCSC_Williams
Simulations of performances of the Cherenkov Telescope Array (CTA). It is specially focused on studying and optimizing the performances of the CTA-US Schwarzschild-Couder Telescope (SCT) for its implementation in the Southern array of CTA. Useful links: CTA (https://www.cta-observatory.org/), Current SCT prototype installed at the Fred Whipple Lawrence Observatory https://cta-psct.physics.ucla.edu/index.html
David Williams
University of California Santa Cruz
Physics
Astronomy and Astrophysics
14
OSG Connect
627
MSU_Szilagyi
Emergence of Life
Robert Szilagyi
Montana State University
Chemistry
Chemistry
14
OSG Connect
295
atlas.wg.Standard-Model
ATLAS Connect team for Standard Model
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
251
atlas.org.bu
ATLAS Connect team for Boston University
Robert William Gardner Jr
Boston University
Physics
High Energy Physics
16
ATLAS Connect
135
XeTPC
Investigate the physics potential of high pressure Xenon TPC for detection of rare processes and develop reconstruction techniques for extremely high granularity detectors.
Adam Para
Fermilab
Scientific Computing Simulation
High Energy Physics
9
Fermilab
594
CompBinFormMod
Computational modeling of the formation of black hole and neutron star binary systems.
Richard O'Shaughnessy
Rochester Institute of Technology
School of Mathematical Sciences
Astronomy and Astrophysics
14
OSG Connect
783
Columbia_Jensen
Bayesian biology models
Johanna Jensen
Columbia University
Department of Ecology, Evolution, and Environmental Biology
Biological and Biomedical Sciences
14
OSG Connect
550122702
NOIRLab_Zhang
Processing astronomical images from the Dark Energy Camera on the Blanco telescope for various research analyses. Perform scientific analyses on clusters of galaxies, features of massive galaxies, and measurements of weak gravitational lensing. Webpage: https://sites.google.com/view/astro-ynzhang/research
Yuanyuan Zhang
NOIR Lab
Community Science and Data Center
Astronomy and Astrophysics
14
OSG Connect
197
cms.org.caltech
CMS Connect at Caltech
Harvey Newman
Caltech
Physics
High Energy Physics
18
CMS Connect
624
Mizzou_RCSS
Research Computing Support Services at the University of Missouri
Timothy Middelkoop
University of Missouri
Research Computing Support Services, Division of IT
Research Computing
14
OSG Connect
506586225
Yale_YCRC
Yale Center for Research Computing - user facilitation
Sinclair Im
Yale University
Center for Research Computing
Computer Science
14
OSG Connect
307
TG-MCB060061N
This proposal is a request for supercomputer resources to carry out computations on five projects. The first project is to study the dynamics of a monoamine transporter in a novel single bilayer system. In this project we are investigating the resetting of the transporter through the movement of potassium ions. The second project is to calculate binding free energies for proposed antidepressant analogs that bind to serotonin. The third project is to investigate the aggregation properties of polyQ peptides. The fourth project is to study the electronic properties of diamond-like semiconductors using band structure methods. The fifth project is to apply quantum monte carlo methods to the study of water dimers and clusters.
Jeffry D. Madura
Duquesne University
Chemistry & Biochemistry
Molecular and Structural Biosciences
13
OSG-XSEDE
421
HRRRMining
I have archived about 30TB (and growing) of output from NOAA's operational High Resolution Rapid Refresh model on an object storage archive system at Utah's Center for High Performance Computing. The challenge is to mine data from such a large data set. Open Science Grid may be a solution for processing this voluminous data set, if questions and data mining objectives can be broken into serial tasks.
Brian Blaylock
University of Utah
Atmospheric Sciences
Earth Sciences
14
OSG Connect
33
TG-IBN130001
The hope for magnetoencephalographic (MEG) measurements has been to produce functional brain mapping with high spatial (mm) and temporal (msec) resolution. Realizing this hope requires answers to these questions: (1) How many sources are active within the brain? (2) Where are they located. (3) What is their time course? MEG Virtual Recording (MVR) provides these while producing noninvasive measures of intracranial neuroelectric currents as if from 2,000,000+ directly implanted electrodes. It does so from single trial (unaveraged) data, has no free parameters, and provides very strong probabilistic measures to validate the existence of each identified source. We have demonstrated efficient implementation of MVR on the Open Sciences Grid. The measured computational load of 400 SU per second of MEG data makes supercomputing essential to practical implementation of MVR. We anticipate that MVR will enable identification of specific neurophysiological biomarkers of a variety of non-structural brain pathologies which have been refractory to date, e.g. concussion, post-traumatic stress disorder.
Donald Krieger
University of Pittsburgh
Neurological Surgery
Biological Sciences
13
OSG-XSEDE
449
BetaDecay
Neutrinoless Double Beta Decay
Liang Yang
University of Illinois Urbana-Champaign
Physics
Physics
14
OSG Connect
2135428230
Internet2_MS-CC
The Minority Serving - Cyberinfrastructure Consortium envisions a transformational partnership to promote advanced cyberinfrastructure capabilities on HBCU, HSI, TCU, and MSI campuses, with data; research computing; teaching; curriculum development and implementation; collaboration; and capacity-building connections among institutions.
Ana Hunsinger
Internet2
MS-CC
Computer and Information Sciences
14
OSG Connect
1389453473
EWMS_Riedel_Startup
To develop an Observation Management System Framework which will help alleviating multiple types of astrophysical data and respective workflow management. The Event Workflow Management System (EWMS)is a workload manager designed for processing events (simulated readouts from a particle physics detector, recorded data points, images, etc.) with complex workflows.
Benedikt Riedel
University of Wisconsin-Madison
Physics
Astrophysics
21
PATh Facility
1671913415
UAB_Worthey
Application of data science, omics, computational biology to understan phenotypic differentiator in human disease.
Elizabeth Worthey
The University of Alabama at Birmingham
Department of Pediatrics and Pathology; CGDS
Biological and Biomedical Sciences
14
OSG Connect
223
cms.org.rutgers
CMS Connect at Rutgers University
Amit Lath
Rutgers, The State University of New Jersey
Physics
High Energy Physics
18
CMS Connect
69
TG-CDA080011
Allocation needed for Campus Champion Activities
Vikram Gazula
University of Kentucky
Center for Computational Sciences
Computer and Information Science and Engineering
13
OSG-XSEDE
261
atlas.org.niu
ATLAS Connect team for Northern Illinois University
Robert William Gardner Jr
Northern Illinois University
Physics
High Energy Physics
16
ATLAS Connect
364
PBOSD
Probability-based structural design has now emerged as the most advanced methodology to design new and retrofit existing structures in the face of uncertainty. The
focus of our research lies at the intersection of the areas of structural engineering and risk engineering against natural hazards (e.g., earthquakes). A large number of computationally-demanding Finite Element simulation jobs need to
be run as part of our research using open source software (e.g., OpenSees, Dakota) and script languages (e.g., Matlab, Python). Thus, the used of high-throughput computing resources will be central for the success of our potentially
high-impact research on probability-based optimum structural design against natural hazards.
Yong Li
University of California, San Diego
Structural Engineering
Civil Engineering
14
OSG Connect
1553547974
NIAID_TBPortals
Training AI models and CT image processing and analysis using these AI models. The collaboration is part of our TB Portals program https://tbportals.niaid.nih.gov/
Darrell Hurt
National Institute of Allergy and Infectious Diseases
Office of Cyber Infrastructure and Computational Biology
Biological and Biomedical Sciences
14
OSG Connect
257
atlas.org.lbnl
ATLAS Connect team for Lawrence Berkeley National Laboratory
Robert William Gardner Jr
Lawrence Berkeley National Laboratory
Physics
High Energy Physics
16
ATLAS Connect
155
KickstarterDataAnalysis
Project Description: Over the past five years, there has been a boom in technology startups that continues to attract more and more talent. While everyone starts with a million-dollar idea, only a few manage to transfer into real innovations and impact our lives. What makes those ideas successful? Can you imagine an app that tells you how innovative your idea is? This project will take a computational approach to the understanding of innovation and develop a machinery to learn from real data to evaluate the creativity of new ideas.
Innovation is a broad topic, constantly discussed in business, economics, sociology, etc. It is such a complex phenomenon that there is no thorough theory about it. Here we will take a combinatorial perspective: an idea is a combination of existing and new knowledge. Hence, the goal is to understand why certain combinations are more interesting than others. Specifically, the first step is to map out our idea space with data from kickstarter, US Patents, and possibly other knowledge databases. The second step is to find interesting patterns, associations and dynamics in this map of knowledge. And finally computational methods will be developed to evaluate the fitness of any idea in a given environment.
Feng Bill Shi
University of Chicago
Computation Institute
Statistics
14
OSG Connect
784
UCBerkeley_Altman
Investigating the electronic properties of materials at low temperatures
Ehud Altman
University of California, Berkeley
Physics
Physics
14
OSG Connect
779
SC_Gothe
Measuring cross section for double charged pion electroproduction off the proton with CLAS at JLab. Needing to simulate events passing through the detector based off previous measurements in order to more accurately determine the acceptance of the detector and thus correct measured raw yields.
Ralf Gothe
University of South Carolina
Department of Physics and Astronomy
Physics
14
OSG Connect
461
BiomedInfo
Development and application of software tools for performing large-scale biomedical informatics on microbial genome sequence data.
Erik Wright
University of Pittsburgh
Bioinformatics
Bioinformatics
14
OSG Connect
377
UADataAnalytics
Enabling scalable data analytics for University of Arizona researchers
Nirav Merchant
University of Arizona
Arizona Research Laboratories
Multi-Science Community
14
OSG Connect
212539179
Cornell_Sandoz
We study bacterial survival. Particularly, we are interested in cell wall modifications in response to changing environments. https://www.ksandozlab.com/new-page-2
Kelsi Sandoz
Cornell University
Population Medicine and Diagnostic Sciences
Biological and Biomedical Sciences
90
atlas.org.fresnostate
Fresno State University's Tier 3 ATLAS group in ATLAS Connect.
Harinder Singh Bawa
Fresno State University
Physics
High Energy Physics
16
ATLAS Connect
99
scicomp-analytics
Development of collection, aggregation, filtering and analysis of probes and metrics as related to distributed computation on the Open Science Grid.
Robert William Gardner Jr
University of Chicago
Computation Institute
Multi-Science Community
14
OSG Connect
319
PreBioEvo
We use simulations Kauffman-like model to study the probability of life forming on other planets. This project is supported by a NASA grant and is part of their Astrobiology mission.
Reference: A. Wynveen, I. Fedorov, and J. W. Halley, Nonequilibrium steady states in a model for prebiotic evolution, Physical Review E 89 , 022725 (2014)
We use simulations of a Kauffman-like model for prebiotic evolution to find the probabilities of lifelike steady states and study their properties. This project is supported by a NASA grant.
References:
A. Wynveen, I. Fedorov, and J. W. Halley, Nonequilibrium steady states in a model for prebiotic evolution, Physical Review E 89 , 022725 (2014) (https://doi.org/10.1103/PhysRevE.89.022725)
B. F. Intoy, A. Wynveen, and J. W. Halley, Effects of spatial diffusion on nonequilibrium steady states in a model for prebiotic evolution, Physical Review E 94 , 042424 (2016) (https://doi.org/10.1103/PhysRevE.94.042424)
J. Woods Halley
University of Minnesota
Physics
Biophysics
14
OSG Connect
567
rencinrig
Project is intended to be used as a test project for a learning experience for the workflows on OSG.
Mert Cevik
Renaissance Computing Institute
Computer Science
Computer Science
14
OSG Connect
81
UCSDEngEarthquake
Earthquake Engineering from UCSD supported users
Frank Wuerthwein
University of California, San Diego
Physics
Engineering
4
UCSD
6
OSG-Staff
Integration and testing of science applications for new users
Frank Wuerthwein
OSG
Computing Sector
Computer and Information Science and Engineering
30
OSG
XRAC
CHTC-XD-SUBMIT
UChicago_OSGConnect_login04
UChicago_OSGConnect_login05
TACC-Stampede2
TG-DDM160003
264
atlas.org.osu
ATLAS Connect team for The Ohio State University
Robert William Gardner Jr
The Ohio State University
Physics
High Energy Physics
16
ATLAS Connect
199
cms.org.ucdavis
CMS Connect at University of California, Davis
John Conway
University of California, Davis
Physics
High Energy Physics
18
CMS Connect
763
TNTech_ITS
Research computing services (within Information Technology Services) and Tennessee Technology University
Mike Renfro
Tennessee Tech University
Information Technology Services
Computer Sciences
14
OSG Connect
801
UCDenver_Kechris
Addressing sparsity in metabolomics data analysis
Katerina Kechris
University of Colorado Denver
Biostatistics and Informatics
Biological Sciences
14
OSG Connect
1045555319
UCDenver_Hartke
Using discharging method to prove upper bounds on coloring parameters for sparse graph classes
Stephen Hartke
University of Colorado Denver
Mathematical and Statistical Sciences
Mathematics
14
OSG Connect
1673675712
Rochester_Mongelli
This will allow for the determination of relative solubility of polymeric materials in alcohol solvents, similar to the shampoo and shaving cream materials. An understanding of the free energy of solvation and surface activity of polyethers and polysilicones will allow for the optimization of alcohol content in such mixtures to get the best bang for the buck in solubilizing and surface tension optimized alcohol-water mixtures with these polymers present.
Guy Mongelli
University of Rochester
Chemical Engineering
Chemical Engineering
14
OSG Connect
142
cms.org.unl
CMS Connect group for UNL
Kenneth Bloom
University of Nebraska-Lincoln
Physics
High Energy Physics
18
CMS Connect
309
AmorphousOrder
Glass-forming liquids exhibit dramatical slowdown upon cooling, which may be controlled by the growing amorphous order that emerges due to the rarefaction of metastable states in the rugged free-energy landscape. The amorphous order is well captured by point-to-set correlations, and their measurements are indispensable in testing ideas surrounding this new order parameter. To attain good statistics on point-to-set observables, however, requires a huge number of independent simulations. Exploration of many parameter ranges -- such as temperature or confinement parameters -- further increases the need for parallel computing. The high throughout computing thus provides an ideal tool for investigating the notion of the growing amorphous order in glassy systems.
Patrick Charbonneau
Duke University
Chemistry
Chemistry
14
OSG Connect
767
Michigan_ARCStaff
Research IT support and advocacy
Todd Raeker
University of Michigan
Advanced Research Computing
Computer Sciences
14
OSG Connect
667
WayneStateU_Majumder
Jetscape heavy ion collision simulations
Abhijit Majumder
Wayne State University
Physics
Physics
14
OSG Connect
348
QGIS
This project is created to explore QGIS and analyze solar suitability in South Carolina.
Patricia Carbajales-Dale
Clemson University
Clemson Center for Geospatial Technologies
Geographic Information Science
14
OSG Connect
110
CotranslationalFolding
There is now a large body of experimental evidence that the ability of many proteins to reach full functionality in a cell depends strongly on the rate at which individual codons are translated by the ribosome during protein synthesis. This project aims to demonstrate that, counter to conventional wisdom, fast-translating codons can help coordinate co-translational protein folding by minimizing misfolding [O’Brien, Nature Comm. 2014]. To do this we will use a two-step approach: First (Aim 1), we will utilize coarse-grained molecular dynamics simulations in combination with a genetic algorithm to find the optimal codon translation rate profile that maximizes the co-translational folding of a protein. And then (Aim 2) mutate, in silico, fast-translating codon positions to slower rates to test, if as predicted, we observe a concomitant decrease in the amount of co-translational folding. The results of this study will provide a new computational tool for the rational design of mRNA sequences to control nascent proten behavior.
Edward O'Brien
The Pennsylvania State University
Chemistry
Biophysics
30
OSG
930981374
CNU_Henry
Research related to biomedical and clinical natural language processing, including information retrieval, information extraction, summarization, and question answering.
Samuel Henry
Christopher Newport University
Department of Physics, Computer Science, and Engineering
Computer and Information Sciences
479
Cdms
CDMS Experiment Cryogenic Dark Matter Search
Joe Boyd
CDMS
CDMS
High Energy Physics
9
Fermilab
554
TG-BIO180012
Automatic knowledge base construction and hypothesis generation antibiotic resistance mechanisms for Escherichia coli
Ilias Tagkopoulos
University of California, Davis
Computer Science
Biological Sciences
13
OSG-XSEDE
77
SoyKB
The Soybean Knowledge Base (SoyKB), a comprehensive all-inclusive web resource for soybean. SoyKB is designed to handle the storage and integration of the gene, genomics, EST, microarray, transcriptomics, proteomics, metabolomics, pathway and phenotype data.
Dong Xu
University of Missouri
Christopher S. Bond Life Sciences Center
Plant Biology
30
OSG
1416814250
NSHE_SCS
Group for University of Nevada staff members to explore the OSPool
Zachary Newell
Nevada System of Higher Education
System Computing Services Group
Research Computing
14
OSG Connect
560
IRIS-CI
Integrity Introspection for Scientific Workflows
Anirban Mandal
University of North Carolina, Chapel Hill
Computer Science
14
OSG Connect
173
numfpi
We are developing a implementation of a Monte Carlo volume rendering method. The primary purpose is to impro
ve the calculation of multiple scattering physics, with possible applications in computer graphics, nuclear physics, and remote s
ensing. The project involves the numerical calculation of a Feynman path integral, which is what most of the computation is devot
ed to, and the primary need for high throughput computing methods.
Jerry Tessendorf
Clemson University
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
590
MCSimulations
The project entails the calculation of the scattering cross sections for the the production of a Higgs boson in association of several jets for current and future collider experiments such as the CERN Large Hadron Collider. Scattering cross section calculation employ Monte Carlo simulation tools such as Herwig 7.
Terrance Figy
Wichita State University
Mathematics, Statistics, and Physics
High Energy Physics
14
OSG Connect
243
pipediffusion
A molecular dynamics study (LAMMPS) of diffusion along the core of a screw dislocation is to be studied.
Panthea Sepehrband
Santa Clara University
Mechanical
Materials Science
14
OSG Connect
697
Rowan_NguyenT
PDE/ODE-based machine learning
Thanh Nguyen
Rowan University
Mathematics
Mathematics
14
OSG Connect
422
electrolytes
Molecular Dynamics simulations of concentrated electrolyte mixtures both in bulk and at interfaces, and spectroscopic characterization of these systems. Electronic Structure calculations used to investigate specific interactions between liquid components
Jesse McDaniel
Georgia Institute of Technology
Chemistry and Biochemistry
Chemistry
14
OSG Connect
252
atlas.org.columbia
ATLAS Connect team for Columbia University
Robert William Gardner Jr
Columbia University
Physics
High Energy Physics
16
ATLAS Connect
762
IU_Tang
Exploring high-throughput mass spec analysis
Haixu Tang
Indiana University
Informatics
Biological Sciences
14
OSG Connect
372255360
Rochester_Liu
I will be using the allocation to help researchers at the University of Rochester to understand how to use XSEDE resources and to test which XSEDE resources best fit their needs.
Baowei Liu
University of Rochester
Dept. of Physics & Astronomy
Training
14
OSG Connect
183
TG-TRA130030
I like to request renewal for my CC allocation. This allocation will help me to provide temporary resources for new users who wish to test XSEDE resources.
Neranjan Edirisinghe Pathirannehelage
Georgia State University
Information Technology
Mathematical Sciences
13
OSG-XSEDE
163
RicePhenomics
Analysis of salinity tolerance in rice.
Harkamal Walia
University of Nebraska-Lincoln
Agronomy
Biological Sciences
14
OSG Connect
478
NDSU-CCAST
As a new contributor of resources to OSG, we would like to introduce our users to the grid and help them transition some of their jobs to OSG resources, as appropriate.
Nick Dusek
North Dakota State University
Center for Computationally Assisted Science and Technology
Multi-Science Community
14
OSG Connect
508
GlobalDH
Test a tool to deal with global data sets.
Kang Wang
University of Colorado Boulder
INSTAAR
Earth Sciences
14
OSG Connect
562
WUSTL_Harris
Effects of simulated interventions on joint loading in patients with bony hip pathologies
Michael Harris
Washington University in St. Louis
School of Medicine Program in Physical Therapy
Physical Therapy
14
OSG Connect
2
OSG-CSC00100
Develop a metric that measures the real similarities and differences between machine learning algorithms (in this case classifiers) based on output behavior. Previous study included 17 representative algorithms and used 30 datasets from the UCI Machine Learning Repository. The main goal of the current effort is to extend the metric using semi-supervised learning techniques. I would also like, if possible, to experiment with more recent datasets beyond what is traditional from the UCI Repository; and to add more algorithms to the study.
George Rudolph
The Citadel
Mathematics and Computer Science
Computer and Information Science and Engineering
30
OSG
105
TG-SEE140006
Description: This proposal requests 20,000 SUs on XSEDE for 20 undergraduate students and mentors participating in the Computational Astronomy & Physics REU Program at the University of North Carolina-Chapel Hill in summer 2014. The time is needed for a computational methods tutorial on the Open Science Grid followed by optional use of the OSG for the students summer research projects, with possible continuing use through January 2014 to enable polishing the projects for presentation at conferences. The projects cover a range of topics in computational astronomy and physics. Details can be found in the supporting material attached.
Sheila Kannappan
University of North Carolina at Chapel Hill
Physics & Astronomy
Physics and astronomy
13
OSG-XSEDE
589
FECliu
Monte Carlo simulations for designing channel error correction codes
Yanfang Liu
New Mexico State University
Electrical Engineering
Engineering
14
OSG Connect
113
TG-STA110011S
renewing project
Stephen McNally
University of Tennessee, Knoxville
NICS
Other
13
OSG-XSEDE
222780249
Caltech_Bouma
Exoplanet and stellar astrophysics research
Luke Bouma
California Institute of Technology
Division of Physics, Mathematics and Astronomy
Astrophysics
1829361616
Kennesaw_RC
Facilitation/Consultation support for faculty with computing and data requirements at Kennesaw State
Ramazan Aygun
Kennesaw State University
Computer Science
Computer Science
14
OSG Connect
704
UWMadison_Tang
Meta-analysis of microbiome studies
Zhengzheng Tang
University of Wisconsin-Madison
Biostatistics and Medical Informatics
Biostatistics
14
OSG Connect
523
DESDM
The Dark Energy Survey (DES) is about to complete its five-year observing program. This consists of a 5000 square-degree wide field survey in 5 optical bands of the Southern sky and a 30 square-degree deep supernova survey with the aim to understand the nature of Dark Energy and the accelerating Universe. DES uses the 3 square-degree CCD camera (DECam), installed at the prime focus of the Blanco 4-m to record the positions and shapes of 300 million galaxies up to redshift 1.4. During a normal night of observations, DES produces about 1 TB of raw data, including science and calibration images, which are transported automatically from Chile to the National Center for Supercomputing Applications in Urbana, Illinois to be archived and reduced. The DES Data Management system (DESDM) is in charge of the processing, calibration and archiving of these data into science-ready data products for analysis by the DES Collaboration and the public.
Don Petravick
National Center for Supercomputing Applications (NCSA)
N/A
Astronomy
14
OSG Connect
115
SbGenome
The Sarcophaga bullata Genome Project seeks to assemble and annotate the genome of Sarcophaga bullata, an important model for cold tolerance and diapause.
Dave Denlinger
Ohio State University
Department of Evolution, Ecology, and Organismal Biology
Bioinformatics
14
OSG Connect
772
PSU_Chen
Computing high-throughput thermodynamic properties and domain structures of lead-free ferroelectric materials and their heterostructures
Long-Qing Chen
Pennsylvania State University
Materials Science and Engineering
Materials Science
14
OSG Connect
488553531
CMU_Viswanathan
Physics-informed machine learning algorithms to facilitate improved prediction of battery performance
Venkat Viswanathan
Carnegie-Mellon University
Department of Mechanical Engineering
Mechanical Engineering
14
OSG Connect
198
cms.org.llnl
CMS Connect at Lawrence Livermore National Laboratory
Doug Wright
Lawrence Livermore National Laboratory
Physics
High Energy Physics
18
CMS Connect
153
ASPU
developing genetic association tests using GWAS data
ilyoup kwak
University of Minnesota
Division of Biostatistics
Bioinformatics
14
OSG Connect
1475351923
TG-CHE210056
Unraveling Crystallization and Phase Transition Processes through Topology, Rare-Event Simulations, and Machine Learning
Jerome Delhommelle
University of North Dakota
Chemistry
Physical Chemistry
14
OSG Connect
212
cms.org.ksu
CMS Connect at Kansas State University
Yurii Maravin
Kansas State University
Physics
High Energy Physics
18
CMS Connect
51
TG-CHE130103
Energy transport in disordered systems coupled to a thermal environment is a topic that is exceedingly important for a diverse set of technological applications including organic photovoltaic solar cells, conducting polymers and a host of others. Unfortunately, at present the dynamics in these systems is not well understood. The primary difficulty is that one must accurately simulate the dynamics of relatively large open quantum systems over lengthy timescales and across a broad range of parameters. Here we request XSEDE resources to focus on two specific questions on the energy transport process that will provide both key fundamental insights, as well as useful design principles to guide the construction of more efficient materials. First, we extend the results of our previous allocation to examine the energy transport in two dimensional thin films with realistic dipolar interactions. These systems are expected to undergo a metal-insulator (Anderson) transition as a function of both the orientation of the molecular dipoles and the strength of disorder. Simulations will be performed to elucidate this phase diagram. Secondly, the nature of the transport in the weak system-bath coupling regime will be explored, wherein the dynamics are largely governed by coherent, quantum effects. The scaling properties of the transport in this regime will be determined, providing insights into the interplay of Anderson localization with the dynamics of open quantum systems.
Jeremy Moix
Massachusetts Institute of Technology
Chemistry
Chemistry
13
OSG-XSEDE
408
JediNetworks
Training recurrent neural nets on various tasks; discretizing the dynamics of the networks and observing changes in network stability, performance and topology.
Bradley Voytek
University of California, San Diego
Neuroscience
Neuroscience
14
OSG Connect
62
DBConcepts
We're conducting a network analysis of a 10% sample (1.6TB; 3.6m files) of the Google Books corpus.
Richard Jean So
University of Chicago
Interdisciplinary
Computer and Information Science and Engineering
14
OSG Connect
149
cgdna
Molecular-level information of DNA at nanometer length scales is of fundamental interest to many aspects of nanotechnology and biology. Molecular models provide a powerful tool to interrogate these systems by providing detailed thermodynamic and kinetic information. Towards this end, this project involves developing highly-accurate coarse-grained models of DNA and using them to study complex nano-scale phenomena.
Juan J de Pablo
University of Chicago
Institute of Molecular Engineering
Molecular and Structural Biosciences
14
OSG Connect
760
Coe_Stobb
Simulations modeling blood flow out of injury sites in the body using ODE and PDE techniques.
Michael T. Stobb
Coe College
Mathematical Sciences
Mathematics
14
OSG Connect
1617146578
UCSD_Fricker
Use satellite remote sensing data to study processes that affect mass loss from the Antarctic Ice Sheet
Helen Fricker
University of California, San Diego
Scripps Institution of Oceanography
Geological and Earth Sciences
14
OSG Connect
494
MicroBooNE
Project entry corresponding to the MicroBooNE VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
592
Venda_Arrey
A Bayesian Modelling approach to Vadose Zone Flow
Ivo Arrey
University of Venda
Hydrology and Water Resourcews
Geological and Earth Sciences
14
OSG Connect
2089895362
CMU_Isayev
Quantum chemical and machine learning insights into supra-molecular organization of molecular crystals.
Olexandr Isayev
Carnegie-Mellon University
Chemistry
Chemistry
600
SDSU_Edwards
Bioinformatics
Rob Edwards
San Diego State University
Viral Information Institute
Bioinformatics
14
OSG Connect
2051232663
UWMadison_Gitter
https://www.biostat.wisc.edu/~gitter/
Anthony Gitter
University of Wisconsin-Madison
Biostatistics and Medical Informatics
Medical (NIH)
513
SMRCNTP
We are exploring the free energy landscape of stacking and columnar liquid assembly in condensed phases of monomer nucleic acids such as ATP and TTP using enhanced sampling methods. We are validating our methods by direct comparison with recent experimental studies of these materials. This work is of relevance to the prebiotic appearance of information carrying polymers such as DNA and RNA.
Joseph Yelk
University of Colorado Boulder
Physics
Biophysics
14
OSG Connect
82
UCSDPhysPart
Non-CMS Particle Physics from UCSD supported users
Frank Wuerthwein
University of California, San Diego
Physics
High Energy Physics
4
UCSD
12
EIC
Electron Ion Collider (EIC) at BNL: Modeling the performance and optimizing the design of the prospected future Electron Ion Collider (EIC) at BNL. https://wiki.bnl.gov/eic/index.php/Main_Page
Tobias Toll
Brookhaven National Laboratory
Physics Department
High Energy Physics
30
OSG
639
Caltech_Rusholme
Joint Survey Processing (JSP) - Pixel-level combination of data from LSST, Euclid, and WFIRST
Benjamin Rusholme
California Institute of Technology
IPAC
Astronomy
14
OSG Connect
1914541499
TG-PHY220016
Benchmarking of 2D Isometric Tensor Network Algorithms. Tensor networks states (TNS) are an essential tool in condensed matter physics for simulating quantum systems on standard, classical computers. In one-dimension, Matrix Product State (MPS) methods are provably accurate at representing a large class of physical states, and efficient algorithms have been developed for finding lowest energy, excited , and time-evolved states. In higher dimensions, however, exactly calculating properties of TNS are provably NP-hard, so approximations must be made. A recent development in two-dimensions (2D) is the isometric tensor network (isoTNS), which places restrictions on the network so that calculations become efficient [1]. We have recently developed algorithms for simulations of 2D networks with a finite by infinite geometry (think of an infinitely long ribbon). It is necessary to now benchmark these methods against existing 1D algorithms applied to 2D systems and determine the system sizes at which these methods outperform their 1D counterparts. The simulation code is written in Python and typically is for a single core. [1] Zaletel, Pollmann; Isometric Tensor Network States in Two Dimensions; Phys. Rev. Lett. 124, 037201 (2020)
Sajant Anand
University of California, Berkeley
Physics
Physics
13
OSG-XSEDE
148
DelhiWorkshop2015
Workshop at Delhi
Robert William Gardner Jr
University of Chicago
Computation Institute
Physics
14
OSG Connect
575
fsuFin
Financial market optimizer machines and option prediction
François Cocquemas
Florida State University
Business
Finance
14
OSG Connect
586
MEEG-group
Interface between MEG/EEG tools and HTCondor
Arno Delorme
University of California, San Diego
Institute for Neural Computation
Neuroscience
14
OSG Connect
650362098
CPSC_5520
Teaching a distributed systems course. Assignments will be at-scale applications including a parallel video rendering pipeline, a genome analysis application, and a text analysis workflow
Nate Kremer-Herman
Seattle University
Computer Science
Computer and Information Science
670
LEARN_CITeam
CI Team for the Lonestar Education and Research Network (LEARN) including CTO staff. http://www.tx-learn.org/
Akbar Kara
Lonestar Education and Research Network
CTOStaff and Cyberinfrastructure Team
Multi-Science Community
14
OSG Connect
751
TG-PHY200004
Toward massively-parallel plasma simulation for low-temperature plasmas
Kentaro Hara
Stanford University
Aerospace Engineering
Physics
13
OSG-XSEDE
571
MFProteins
Simulations of mini-fluorescent proteins
Colin Smith
Wesleyan University
Chemistry
Chemistry
14
OSG Connect
227
cms-org-baylor
CMS Connect at Baylor University
Kenichi Hatakeyama
Baylor University
Physics
High Energy Physics
18
CMS Connect
634
Internet2
Cloud and OSG Integration
Sara Jeanes
Internet2
other
Infrastructure Development
14
OSG Connect
981111279
BCBB_NIAID
Group for staff/members of the Bioinformatics and Computational Biosciences Branch (BCBB) at NIAID/NIH.
Darrell Hurt
National Institute of Allergy and Infectious Diseases
Office of Cyber Infrastructure and Computational Biology
Bioinformatics
14
OSG Connect
346
REDTOP
High intensity frontier experiment searching for physics beyond the Standard Model
Corrado Gatto
Fermilab
Particle Physics
High Energy Physics
14
OSG Connect
758
CHTC-Staff
Group for CHTC staff who have OSG accounts
Miron Livny
University of Wisconsin-Madison
Computer Sciences
Computer Sciences
14
OSG Connect
Other
CHTC-ITB-submittest0000
CHTC-ITB
glow
XRAC
CHTC-XD-SUBMIT
UChicago_OSGConnect_login04
UChicago_OSGConnect_login05
TACC-Stampede2
TG-DDM160003
786
PRP
The PRP is a partnership of more than 50 institutions, led by researchers at UC San Diego and UC Berkeley. The PRP builds on the optical backbone of Pacific Wave, a joint project of CENIC and the Pacific Northwest GigaPOP (PNWGP) to create a seamless research platform that encourages collaboration on a broad range of data-intensive fields and projects.
Thomas A. DeFanti
University of California, San Diego
Calit2
Computer Science
14
OSG Connect
1315886390
MIT_Takei
I am working on models for quantifying the effects on the change of financial regulations
Ikuo Takei
Massachusetts Institute of Technology
Global Programs
Finance
1411921077
UCF_Khan
Investigating the ability of neural networks to represent functions in the context of approximation theory. We seek to uncover areas of scientific computing in which neural networks provide a 'better-than-nothing' approximation of a solution in high-dimensional problems wherein classical scientific computing methods fail. The primary area of investigation is the ability of a neural network to capture inherent low-dimensional structure present in high-dimensional functions.
Fahad Khan
University of Central Florida
Research Cyberinfrastructure
Mathematics and Statistics
491
Minerva
Project entry corresponding to the Minerva VO.
Gabriel Nathan Perdue
Fermilab
N/A
High Energy Physics
9
Fermilab
106
TG-CHE140094
Hybridization and denaturation transitions between DNA duplex and single stranded forms will be studied using Monte Carlo molecular simulation and a coarse-grained model. Short oligomers, between 10 and 25 bases in length, will be studied for one to two sequences, for cases where both strands are in solution as well as where one strand is bound to a surface as a model for a DNA microarray. The effects of temperature and of surface binding density will also be studied, and the results analyzed in terms of structural effects and hydrogen bonding patterns within the duplex.
John Stubbs
University of New England
Chemistry and Physics
Chemistry
13
OSG-XSEDE
469
popage
Using FSPS estimate the age of a stellar population from its SED. This will be applied to improving SN Ia distance measurements.
Benjamin Rose
University of Notre Dame
Physics
Astrophysics
14
OSG Connect
645
TG-TRA120031
Campus Champions Renewal
John Burkman
Louisiana School for Math, Science, and the Arts
Mathematics
Advanced Scientific Computing
13
OSG-XSEDE
55
AMFORA
Amfora is a POSIX-compatible parallel scripting framework that lets users run existing programs in parallel with data stored in RAM on distributed platforms: e.g. clouds, clusters, supercomputers.
Ian Foster
University of Chicago
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
178
Phylo
In this project, we design, implement, and test new methods for phylogenomics analyses. The goal of phylogenomics, as used here, is to estimate a species tree from genomic data. The ultimate goal of this line of research is reconstructing the tree of life.
Siavash Mirarab
University of California, San Diego
Electrical and Computer Engineering
Bioinformatics
14
OSG Connect
773
Syracuse_Brown
Gravitational-wave astronomy and astrophysics.
Duncan Brown
Syracuse University
Physics
Astrophysics
14
OSG Connect
324
snada
Simulate social networks to analyze statistical properties.
Wei Wang
University of Central Florida
Psychology
Multi-Science Community
14
OSG Connect
36
TG-IRI130016
Analysis of geospatial imagery has become a promising approach for characterizing Weapons of Mass Destruction (WMD) proliferation. The goal of this project is to design algorithms and computer executable that can extract man-made objects (e.g., building, road, gate, etc.) from high-resolution images (recording the boundary and location, and possible type).
Joseph Cohen
University of Massachusetts Boston
Computer Science
Information, Robotics, and Intelligent Systems
13
OSG-XSEDE
268
atlas.org.slac
ATLAS Connect team for SLAC National Accelerator Laboratory
Robert William Gardner Jr
SLAC National Accelerator Laboratory
Physics
High Energy Physics
16
ATLAS Connect
330475465
ASU_RCStaff
Group for ASU research computing staff
Douglas M. Jennewein
Arizona State University
Research Computing
Research Computing
14
OSG Connect
242
atlas.wg.Exotics
We study exotics.
Robert William Gardner Jr
ATLAS
ATLAS
High Energy Physics
16
ATLAS Connect
977036130
GPN
GPN regional workflow development efforts to encourage new projects.
James Deaton
Great Plains Network
Research Computing
Multidisciplinary
14
OSG Connect
388815060
CMB_Petravick
The CMB-S4 project is prototyping processing and data flow on the FABRIC testbed https://portal.fabric-testbed.net/. We are studying the use of HTCondor on FABRIC VM nodes in scenarios where data would arrive over high speed networks.
Donald Petravick
University of Illinois Urbana-Champaign
National Center for Supercomputing Applications (NCSA)
Astronomy
14
OSG Connect
1463792973
UWMadison_Livny
http://chtc.cs.wisc.edu/
Miron Livny
University of Wisconsin-Madison
Computer Sciences
Computer & Information Science & Engineering
398
Nipyperegtest
Regression testing of various brain imaging tools
Satrajit Ghosh
Massachusetts Institute of Technology
McGovern Institute for Brain Research
Neuroscience
14
OSG Connect
1620059748
ND_Lalor
Conduct research on efficient training for large language models and other analytics methods. My research uses GPU compute to evaluate the efficiency improvements of LLM training modifications to develop smaller, more efficient, and easier-to-train models that reduce the computational and cost burden.
John Lalor
University of Notre Dame
Department of IT, Analytics, and Operations
Computer and Information Sciences
731
ASU_Jacobs
Simulations of radio interferometers
Daniel Jacobs
Arizona State University
School of Earth and Space Exploration
Astronomy
14
OSG Connect
445
U5Mortality
Analyze U-5 mortality convergence and compression in developed and developing countries.
Analyze lifespan inequality in U-5 mortality and how it correlates with other sources of inequality across and within countries.
Shripad Tuljapurkar
Stanford University
Biology
Biological Sciences
14
OSG Connect
673
TG-CHE190046
Spectroscopic signatures of enhanced coherent transport in chemically modified light-harvesting systems
Jonathan Fetherolf
University of Chicago
Chemistry and James Franck Institute
Chemistry
13
OSG-XSEDE
610
UMT_Warren
Public health projects such as the effect of wildfires on the respiratory health of children in rural vs urban areas, hydrology modeling in the continental US using realtime GIS data and genetic and migratory patterns in animal populations whose movement is impacted by man-made structures.
Allen Warren
University of Montana
School of Public and Community Health Services
Mathematics and Statistics
14
OSG Connect
472
Shortrunjobs
I'm working with researchers at FSU to show them how to use docker, singularity and OSG and I'd like to be able to submit an example job during some tutorials. I'll keep the runtime to just a few seconds so as to not use up resources.
Donny Shrum
Florida State University
Research Computing Center
Computer and Information Science and Engineering
14
OSG Connect
79
UCSDPhysAstroTheo
Theoretical Astrophysics from UCSD supported users
Frank Wuerthwein
University of California, San Diego
Physics
Astrophysics
4
UCSD
432
Bioconductor
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Martin Morgan
Roswell Park Cancer Institute
Biostatistics and Bioinformatics
Bioinformatics
14
OSG Connect
514
SMOTNT
Current model tracks the status of every single mRNA, ribosome, tRNA molecules during transcription and translation processes. The activities of these molecules are mainly governed by experimentally determined parameters such as their abundances and diffusion rates, as well as gene-specific rates for transcription, mRNA decay and translation.
Tongji Xing
Rutgers, The State University of New Jersey
Genetics Department
Bioinformatics
14
OSG Connect
665
WeNMR
WeNMR is a Virtual Research Community supported by EGI. WeNMR aims at bringing together complementary research teams in the structural biology and life science area into a virtual research community at a worldwide level and provide them with a platform integrating and streamlining the computational approaches necessary for data analysis and modelling.
Alexandre Bonvin
Utrecht University
N/A
Biological Sciences
73
ENMR
702
UWMadison_Wei
Economic modeling
Shiyan Wei
University of Wisconsin-Madison
Economics
Economics
14
OSG Connect
840
UNL_Zhang
Designing statistically rigorous and physically sound models to integrate genome sequences, expression profiles, molecular interactions, and protein structures
Chi Zhang
University of Nebraska - Lincoln
Biological Sciences
Biological Sciences
14
OSG Connect
612
UCSD_Grover
Use Monte Carlo simulation to study Newmann Moore model
Tarun Grover
University of California, San Diego
Physics
Physics
14
OSG Connect
793
Michigan_Seelbach
Automating movement and identification of fish in restored wetland areas
Paul Seelbach
University of Michigan
School for Environment and Sustainability
Earth and Ocean Sciences
14
OSG Connect
344
GTConvertHTC
help GT researchers convert their existing projects into HTC workloads
Mehmet Belgin
Georgia Institute of Technology
Advanced Research Computing
Multi-Science Community
14
OSG Connect
357
QMC
Our project uses Quantum Monte Carlo (QMC) methods for energy calculations on molecular systems of interest.
Andrew Powell
Missouri University of Science and Technology
Chemistry
Chemistry
14
OSG Connect
635
MSU_Berz
Nonlinear beam dynamics simulations of the Muon g-2 Experiment at Fermilab
Martin Berz
Michigan State University
Physics
Physics
14
OSG Connect
1918053794
TG-PHY210083
Study the nonlinear elastic behavior of nanomaterials using a polynomial based constitutive equation to model the behavior of the materials.
Senthil S. Vel
University of Maine
Mechanical Engineering
Materials Science
14
OSG Connect
283
atlas.org.wisc
ATLAS Connect team for University of Wisconsin
Robert William Gardner Jr
University of Wisconsin-Madison
Physics
High Energy Physics
16
ATLAS Connect
1838383619
TG-TRA220011
Campus Champions allocation for Lehigh University
Alexander Pacheco
Lehigh University
Library & Technology Services
Training
14
OSG Connect
1060226383
UTA_Cuntz
python simulations that test stability and the orbital dynamics of multi body systems
Manfred Cuntz
University of Texas at Arlington
Physics
Astronomy and Astrophysics
14
OSG Connect
167
BioGraph
Constructing gene interaction graphs at high scale
Alex Feltus
Clemson University
Genetics & Biochemistry
Biological Sciences
14
OSG Connect
313
TG-AST150046
We are using several large codes to search the photometric database from the Kepler satellite for stars that exhibit flares and starspots, to characterize the flare and starspot behavior and to extract information on starspot locations and properties using transiting planets as probes of stellar surface brightness variations. The XSEDE resources will enable this project to proceed much more quickly than with the resources at our home institutions.
Suzanne Hawley
University of Washington
Astronomy
Physics
13
OSG-XSEDE
511
MINT
The Model INTegration (MINT) project will develop a modeling environment which will significantly reduce the time needed to develop new integrated models, while ensuring their utility and accuracy.
Mats Rynge
ISI
Computer Science
Earth Sciences
14
OSG Connect
238
cms.org.buffalo
CMS Connect at State University of New York at Buffalo
Avto Kharchilava
State University of New York at Buffalo
Physics
High Energy Physics
18
CMS Connect
549
TG-PHY130048
Campus Champion Renewal
Dodi Heryadi
University of Notre Dame
Advanced Scientific Computing
13
OSG-XSEDE
441118516
xenon
The XENON Dark Matter Experiment located at the Gran Sasso Laboratories (INFN, Italy), is currently the leader world project searching for the so called Dark Matter, something which is completely different from ordinary matter. This Dark Matter is not (as the name hints) visible, but it should pervade the entire Universe. Its presence has been confirmed by different experimental evidences, however its intrinsic nature is one of the big puzzle of Modern Physics. The XENON Experiment could reveal the nature of the DM looking at the possible interactions of the DM with ordinary matter, for instance with the Xenon, a noble gas been liquified at very low temperature. The study of the background signal, from the environment and from the materials that make up the new detector containing the Xenon, is essential to understand the detector's behavior and its implications on its performances.
Luca Grandi
University of Chicago
Physics
Astrophysics
29
RDCEP
Robust Decision Making on Climate and Energy Policy (RDCEP)
The Center for Robust Decision Making on Climate and Energy Policy conducts research in four main areas:
* Improving the fidelity of models used to forecast the impact of policies on future economic and climatic conditions. Many of the most decision-relevant aspects of climate and energy policy - for example, climate impacts and technological advances - are poorly or not at all represented in current policy analysis tools. The Center will build representations of the most important processes and increase model detail and resolution.
* Quantifying sensitivities and uncertainties in the parameters, processes, and impacts in models. RDCEP will develop methods to characterize the dependence of model output on input, parameter, and model uncertainty; incorporate these uncertainties in models; and study how to communicate probabilistic model output to decision makers.
* Identifying robust decisions in the face of uncertainty. The best policy is not necessarily that which produces the maximum return if all assumptions made are borne out, but the one that balances return and risk in the face of many uncertainties. The Center will develop models to identify robust strategies that perform well over a wide range of scenarios.
* Developing improved computational methods and numerical methods required to achieve these goals. New parallel stochastic dynamic programming, robust optimal control, and numerical optimization methods able to make full use of modern supercomputers will allow tools developed at the Center to incorporate sectoral and process detail and explore uncertainty, in ways not previously possible.
Ian Foster
University of Chicago
Computation Institute
Economics
14
OSG Connect
25
PathSpaceHMC
The goal of this research is to develop a computational tool that can uncover the pathway and the transition states that exist when a molecule changes conformation or when it chemically changes. In many such circumstances, a process must overcome an energy barrier before proceeding to completion. If the size of the barrier is large compared to the available thermal energy, a process must rely on the occurrence of one or more rare events. For such circumstances, one would like to understand the reaction pathways so as to improve yields, or as in the case of protein folding, to understand the intermediate states. Many simple processes have been explored using theoretical tools such as molecular dynamics, where the movements of individual atoms are calculated. However, when the barrier is large, crossing the relevant barrier is indeed a very rare event. Although computer speeds have been doubling every 18 months (a consequence of Moore's law), the exponentially long waiting times necessary for barrier hopping pushes the required computational effort out of the feasibility range for all but the simplest models. To explore these barrier-limited processes, we are developing a novel computational technique to sample the paths themselves in a thermodynamically significant manner.
Frank Pinski
University of Cincinnati
Physics
Computational Condensed Matter Physics
14
OSG Connect
137630307
NOAA_DucharmeBarth
NOAA Fisheries uses stock assessments to monitor the condition of nearly 500 fish stocks and stock complexes (groups of similar stocks managed together). Stock assessments are scientific efforts that involve data collection, data processing, and mathematical modeling that estimate the health and size of a fish stock, measure how fishing affects the stock, and project harvest levels that achieve the largest sustainable long-term yield. Stock assessments are the backbone of sustainable fisheries management. These assessments allow us to evaluate and report the status of managed fisheries, marine mammals, and endangered/threatened species under the authorities of the Magnuson-Stevens Fishery Conservation and Management Act, the Marine Mammal Protection Act, and the Endangered Species Act. The outcome of this project will be to develop and document a workflow for running existing stock assessment platforms (e.g. StockSynthesis, Multifan-CL, Beaufort Assessment Model, etc.) on a distributed computing system in order to facilitate the script based, ‘simultaneous’ exploration of multiple alternative model configurations. This workflow can be used to develop a stock assessment in either the single best base case or ensemble model framework. This project will support hypothesis exploration, model ensembling, and improved automation of stock assessments.
Nicholas Ducharme-Barth
National Oceanic and Atmospheric Administration
Pacific Islands Fisheries Science Center
Natural Resources and Conservation
14
OSG Connect
459
LGAMUT
Simulations for developing a kernel based statistical methodology.
Debashis Ghosh
University of Colorado Denver
Biostatistics
Bioinformatics
14
OSG Connect
311
TG-GEO150003
The goal of this project is to implement Sol (a set of programs to compute solar insolation on complex landscapes and the energy available to drive weathering). These programs current run on University of Arizona machines but we wish to test their portability to OpenTopography.org using SDSC resources.
Jon Pelletier
University of Arizona
Geosciences
Geographic Information Science
13
OSG-XSEDE
296
atlas.org.Tau
ATLAS Connect team for Tau
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
843
UTulsa_Booth
Research within the lab focuses on evolutionary biology, molecular ecology, and population genetics. Broadly our interests fall into two categories: the evolutionary forces driving population differentiation and dynamics within mosaic landscapes, and the evolution and ecological significance of alternative reproductive strategies. We investigate these in a variety of systems, including mammals, reptiles, amphibians, and insects, and address them using high resolution molecular markers. Much of this work is in collaboration with other researchers, maximizing the resources and expertise available to a given question.
Warren Booth
University of Tulsa
Biological Sciences
Biological Sciences
14
OSG Connect
1176451466
Spelman_Tekle
My lab implements the basic principles of evolution to study the diversity, origin and relationships of medical and nonmedical microbes.
Yonas Tekle
Spelman College
Biology
Biological and Biomedical Sciences
14
OSG Connect
424
Specppxf
Robust statistical inference of the kinematics from astrophysical spectra using Monte Carlo methods
Alabi Adebusola
University of California, Santa Cruz
Department of Astronomy and Astrophysics
Astrophysics
14
OSG Connect
203
cms.org.fairfield
CMS Connect at Fairfield
Dave Winn
Fairfield
Physics
High Energy Physics
18
CMS Connect
37
TG-MCB100109
The purpose of this proposal is to renew our XRAC Allocation TG-MCB100109. During the past year, this allocation has provided us with sufficient resources to further optimize our weighted ensemble path sampling software for the efficient simulation of rare events and to apply the software to the simulation of association kinetics for a model protein-peptide system (the MDM2-p53 peptide complex). We now request a larger allocation to enable the application of the weighted ensemble approach to explicit solvent simulations of binding events for a model protein-protein complex (barnase-barstar complex) with rigorous calculation of association rates. This allocation will also enable the QM/MM simulations of a diffusion-controlled chemical reaction in solution (the addition of azide ion to a series of triphenylmethyl-derived cations) with the aid of the weighted ensemble approach. These applications will be important milestones two grand challenges in computational chemistry: 1) the simulation of protein binding events, and 2) the simulation of chemical reactions in solution. It would not be possible to make meaningful progress on these simulations without the requested allocation on the XSEDE resources.
Lillian Chong
University of Pittsburgh
Chemistry
Molecular and Structural Biosciences
13
OSG-XSEDE
837
UNL_Yang
Mediation analysis of agronomic traits in maize
Jinliang Yang
University of Nebraska - Lincoln
Agronomy and Horticulture
Agricultural Sciences
14
OSG Connect
834
TG-BIO210118
Prediction accuracy of R-loop formation along the human genome
Gerald Quon
University of California, Davis
Molecular and Cellular Biology
Genetics
13
OSG-XSEDE
1739496113
TG-TRA090005
Campus Champion Allocation for University of Michigan
Michelle Johnson
University of Michigan
Advanced Research Computing - Technology Services
Training
14
OSG Connect
495
Nova
Project entry corresponding to the Nova VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
694
UMassAmherst_Sloutsky
Evolutionary reconstructions and molecular simulations of extant and ancestral proteins.
Roman Sloutsky
University of Massachusetts Amherst
Biochemistry and Molecular Biology
Biological Sciences
14
OSG Connect
1951126972
PSU_Yamamoto
A machine learning-based 3D reconstruction of highly porous cement samples cured in a microgravity environment is being pursued. The approach follows a deep learning-based framework based on the solid texture synthesis method, widely adopted in the computer graphics community. Preliminary results https://doi.org/10.2514/6.2023-2025 showed promising results, and with increased computational resources, larger exemplars higher resolution will be used for 3D reconstruction.
Namiko Yamamoto
Pennsylvania State University
Aerospace Engineering
Aerospace, Aeronautical, and Astronautical Engineering
14
OSG Connect
289
atlas.wg.Heavy-Ions
ATLAS Connect team for Heavy Ions
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
407
Leaderbipartite
Leader-Milicevic-Tan asked how many products of complete bipartite graphs are needed to decompose the edge set of K_3 x K_n. Doing this with 2*(n-1) is trivial, here we use simulated annealing to search for a better construction.
Jozsef Balogh
University of Illinois Urbana-Champaign
Mathematics
Mathematical Sciences
14
OSG Connect
1749364515
UMontana_Roy
1) Virtual screening - Computational or virtual screening of molecules can accelerate drug development programs. We have developed a virtual screening method to screen billions of molecules for hit generation against specific protein targets. We want to develop the method further and also want to use the method to develop hits against specific proteins, such as the one announced in this competition. https://cache-challenge.org/ 2) Entropy from surface properties - Calculating entropy is tricky, as, in principle, it requires sampling vast phase space to count all available microstates. We are developing a method for calculating the entropy of small molecules from their surface properties. Such a method will benefit computational chemistry, especially the virtual screening community. https://www.biorxiv.org/content/10.1101/2021.05.26.445640v1.abstract 3) Transferability of polygenic risk scores (PRS) - PRS is a useful tool to estimate one's health condition propensity from their genetic makeup. Historically, most of the PRS models were built from European ancestry samples. We are working on a network model to identify the best way to transfer a PRS model from the population it was developed for to another population not included in the study.
Amitava Roy
University of Montana
Department of Biomedical and Pharmaceutical Sciences
Biological and Biomedical Sciences
655
JAM
Jefferson Lab's Angular Momentum collaboration
Thomas Britton
Jefferson Lab
Physics
Nuclear Physics
99
JLab
691
HPS
Jefferson Lab's Heavy Photon Search project
Thomas Britton
Jefferson Lab
Physics
Nuclear Physics
99
JLab
385
AdHocComm
We are evaluating heuristic approaches from active learning for communicating partial policy information in ad hoc teamwork scenarios.
Trevor Santarra
University of California, Santa Cruz
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
613
UMN_RF_Staff
Research Facilitation support at the University of Minnesota
Charles Nguyen
University of Minnesota
Office of Information Technology
Computer and Information Services
14
OSG Connect
1183071664
VT_Riexinger
Virginia Traffic Cameras for Advanced Safety Technologies (VTCAST) - analyzing driver behavior from one year of VA traffic camera video
Luke Riexinger
Virginia Tech University
Biomedical Engineering and Mechanics
Biomedical Engineering
14
OSG Connect
43
TG-PHY110015
We propose to investigate signatures for the discovery of new physics at the LHC which would run at a center of mass energy of either 7 TeV, 8 TeV, 10 TeV or 14 TeV. Our goal is to first study the Standard Model background at these energies, and then develop analyses that strongly highlight and discriminate theories of new physics. We will use our actively developed software, FastSUSY, to carry out Bayesian analyses that estimate the parameters of the various models of new physics, in light of the most recent data. We also propose to study topological invariants of manifolds that are important in String Theory, searching for correlations to algebraic structures relevant to model building, and compute the properties of the vacua associated with these geometries. Additionally, we wish to extend our analyses to models of supergravity that including CP-violating phases. Our total request is for 7 million SUs and 5 TB of disk space for the proposed projects.
Pran Nath
Northeastern University
Physics
Physics and astronomy
13
OSG-XSEDE
657
GATech_Brown
Brain imaging to understand memory and spatial navigation
Thackery Brown
Georgia Institute of Technology
Psychology
Neuroscience
14
OSG Connect
100
FFValidate
This project will involve running molecular dynamics simulations to validate new protein force fields. We will be comparing the results of the simulations to experimental protein crystal structures and nuclear magnetic resonance (NMR) measurements.
Vijay Pande
Stanford University
Department of Chemistry
Chemistry
14
OSG Connect
18
CompChem
Modeling and simulation of molecules.
Chaoren Liu
Duke University
Chemistry
Chemistry
14
OSG Connect
526815136
MIT_Kardar
Simulation of large-scale evolutionary dynamics
Mehran Kardar
Massachusetts Institute of Technology
Department of Physics
Physics
14
OSG Connect
761755652
UOregon_Shende
The project will evaluate the feasibility of using Singularity containers from the Extreme-scale Scientific Software Stack (E4S)[https://e4s.io] in the Open Science Grid to support HPC and AI/ML workflows. E4S includes support for 100+ HPC products (e.g., TAU, Trilinos, PETSc, OpenMPI, MPICH, Kokkos, HDF5) and AI/ML products (e.g., TensorFlow, PyTorch) optimized for GPUs from three vendors (Intel, AMD, and NVIDIA). It supports LLVM compilers, vendor compilers (NVHPC, oneAPI, ROCm hipcc), on multiple architectures (including x86_64, ppc64le, and aarch64).
Sameer Shende
University of Oregon
Performance Research Laboratory, Oregon Advanced Computing Institute for Science and Society (OACISS)
Computer and Information Services
14
OSG Connect
467
UPCDOSAR
Researchers from UNAL will be using OSG and running example jobs on Monte Carlo simulations, they will be submitting jobs related to bit patterned media, following this work http://www.sciencedirect.com/science/article/pii/S1386947715303222, and will also be submitting jobs related to research in critical phenomena, similar to what was done here: http://www.sciencedirect.com/science/article/pii/S0304885316324933?via%3Dihub and here http://www.sciencedirect.com/science/article/pii/S0304885316320169?via%3Dihub
Rob Quick
Indiana University
Research Technologies
Computational Condensed Matter Physics
14
OSG Connect
791914894
TAMU_Rathinam
Develop novel algorithms for path planning of multi-agent systems.
Sivakumar Rathinam
Texas A&M University
Department of Mechanical Engineering
Engineering
14
OSG Connect
503
Minos
Project entry corresponding to the Minos VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
530
DemoSims
Population demographics
Jeffrey D Jensen
Arizona State University
Life Sciences
Evolutionary Biology
14
OSG Connect
849
USU_Kaundal
Biological data is accumulating faster than people’s capacity to analyze them. Our research interests and goals revolve around mitigating this issue in the context of “information to inference” scope. At USU, Dr. Kaundal has developed an independent and collaborative research program in bioinformatics, primarily focusing on computational mining of large multi-dimensional -omics datasets, and computational modeling using supervised (Machine Learning) and unsupervised (Bayesian-based) learning. Our group is actively developing novel tools and software to apply the gained knowledge towards organismal improvement. Research in KAABiL laboratory generally falls under the following major program objectives: http://bioinfo.usu.edu/research
Rakesh Kaundal
Utah State University
Bioinformatics
Biological Sciences
14
OSG Connect
766
Michigan_Brines
Assessing & Communicating Climate and Water Ecosystem Services of the City of Ann Arbor Greenbelt Program
Shannon Brines
University of Michigan
The School for Environment and Sustainability
Natural Resources and Conservation
14
OSG Connect
1767081475
UCSD_Gilson
We use theoretical, computational, informatic, and experimental approaches to evaluate and advance the methods of computer-aided drug design. We also work on drug discovery projects and study molecular motors and other nonequilibrium systems.
Michael Gilson
University of California, San Diego
Skaggs School of Pharmacy & Pharmaceutical Sciences
Chemistry
14
OSG Connect
647811416
UTA_Jones
works on the NEXT neutrinoless double beta decay experiment: https://next.ific.uv.es/next/ which is an international collaboration. The experiment is trying to determine if the neutrino is its own anti-particle.
Ben Jones
University of Texas at Arlington
Physics
Physics
294
atlas.wg.SUSY
ATLAS Connect team for SUSY
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
607
LSUHSC_Lin
LASSO Variable Selection for Genetic Interaction Models
Hui-Yi Lin
Louisiana State University Health Sciences Center
Biostatistics
Biostatistics
14
OSG Connect
731
UCLA_Huang
Studying $\Omega$-hadron correlation to search for signatures of baryon junction mechanisms at RHIC BES energies.
Huan Zhong Huang
Arizona State University
Physics and Astronomy
Astronomy
14
OSG Connect
741
MFEKC
Molecular-Free-Energy-Computing
Glen Hocky
New York University
Chemistry
Chemistry
14
OSG Connect
436
MarLab
Doing RNA-seq analysis to understand biomolecular systems.
Jessica Mar
Albert Einstein College of Medicine
Systems and Computational Biology
Bioinformatics
14
OSG Connect
409
WheatGenomics
Analysis of wheat genome and transcriptome datasets
Ghana Challa
South Dakota State University
Biology
Bioinformatics
18
CMS Connect
34
TG-PHY120014
The discovery of a Higgs-like particle, announced in June 2012 by CERN, was a defining moment in the field of high energy physics. The excitement of this finding was felt world-wide and is a breakthrough in our understanding of the Universe at a fundamental level. Saying therefore that we now live in a post-Higgs era in high energy physics is no exaggeration. This breakthrough by the Large Hadron Collider (LHC) is just a first step towards testing much extensive theories such as supersymmetry and grand unification. Computing tools played an important role in the discovery of the Higgs and the need for these tools to explore ideas beyond the Standard Model is ever increasing. Resources like XSEDE therefore provide an opportunity to use cutting edge computing tools in order to explore novel ideas in high energy physics. Our startup allocation of 150,000 SU's resulted in four peer reviewed publications. With the second allocation of 3 million SUs our group managed to complete 10 articles out of which 7 have been published in peer reviewed journals and three are in process. The data for two other projects have been collected. These projects resulted from the consumption of only 32% of the total SUs that were allocated. Our consumption of the SUs was much less than anticipated since we have improved the computing techniques we use in our projects. We are therefore requesting an extension of our current SUs since a surplus of SUs is always useful for us to pursue projects even if the SU requirement is high.
Qaisar Shafi
University of Delaware
Physics and astronomy
Physics and astronomy
13
OSG-XSEDE
703410343
NCSU_Barroso
Biomolecular interactions have been core pillars of our research. We are involved in developing and applying new computational technologies and offering a rational computational-based approach to the study of protein systems and the discovery of novel therapeutic agents (e.g. antibodies), biomarkers, and proteins for specific applications including key disease-related protein mechanisms.
Fernando Luis Barroso da Silva
North Carolina State University
Department of Chemical and Biomolecular Engineering
Biological and Biomedical Sciences/Biophysics
14
OSG Connect
707
GATech_Taboada
IceCube neutrino sources search
Ignacio Taboada
Georgia Institute of Technology
Physics
Physics
14
OSG Connect
78
TG-CCR130001
I am applying for a renewal of campus champion allocations for Stanford.
Ruth Marinshaw
Stanford University
Research Computing
Training
13
OSG-XSEDE
1191276236
UCBerkeley_Zaletel
Tensor networks provide an efficient approximation to quantum many-body wavefunctions and a controllable method to simulate quantum computing on classical hardware. We apply these techniques to problems in condensed matter physics and quantum error correction.
Mike Zaletel
University of California, Berkeley
Physics
Condensed Matter Physics
14
OSG Connect
821
UEdinburgh_DUNE
The Deep Underground Neutrino Experiment is an international flagship experiment to unlock the mysteries of neutrinos.
Stefan Söldner-Rembold
University of Edinburgh
Physics and Astronomy
Physics
14
OSG Connect
765259767
UConn_Alpay
Our team of scientists uses computational and theoretical methodologies to understand and address fundamental problems in materials science and engineering. Collectively, we have a broad spectrum of research interests with myriad applications. We use our understanding to design advanced materials that impact the way we live, including functional materials, smart materials, aerospace, nanostructured materials and materials for energy efficiency. https://alpay.ims.uconn.edu/
Pamir Alpay
University of Connecticut
Materials Science and Engineering
Materials Science
588
KoBIV
Bayesian Instrumental Variable Regression
Stanley Iat-Meng KO
University of Macau
Finance
Finance
14
OSG Connect
45
TG-TRA100004
Swarthmore College Campus Champion Renewal
Andrew Ruether
Swarthmore College
ITS
Training
13
OSG-XSEDE
493
Mu2e
Project entry corresponding to the Mu2e VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
249
atlas.org.bnl
ATLAS Connect team for Brookhaven National Laboratory
Robert William Gardner Jr
Brookhaven National Laboratory
Physics
High Energy Physics
16
ATLAS Connect
437
a1synchrony
We investigate how synchronous population activity arise in spiking dynamics of the sensory and other cortical areas. We especially focus on how primary auditory cortex modulate dynamical timescales during spontaneous bump dynamics in quiet wake condition and up and down states in anesthetized and sleep conditions.
Yashar Ahmadian
University of Oregon
Institute of Neuroscience
Neuroscience
14
OSG Connect
797
Fairfield_Kubasik
I seek to perform molecular dynamics simulations using Gromacs. Specifically, I seek to run trajectories of short peptide molecules in various solvents in order to compute infrared spectra and configurational free energy differences.
Matthew Kubasik
Fairfield
Department of Chemistry & Biochemistry
Chemistry
14
OSG Connect
841
UNL_Cui
Understanding complex biological systems, e.g. human diseases such as obesity and cancer, through data integration, computational modeling and knowledge discovery, to systematically understand the alterations of cells and organisms in response to environmental stimuli, and to elucidate the molecular interaction network involved in complex biological processes.
Juan Cui
University of Nebraska - Lincoln
Biological Sciences
Biological Sciences
14
OSG Connect
478994236
Caltech_Kanner
I am interested in learning to use OSG resources for LIGO data analysis. I am especially interested in parameter estimation jobs using bilby or BayesWave. See https://gwosc.org for more information.
Jonah Kanner
California Institute of Technology
LIGO Laboratory
Physics
14
OSG Connect
583
AMNH_Smith
Integrative Models of Avian Speciation
Brian Smith
American Museum of Natural History
Ornithology
Biological and Biomedical Sciences
14
OSG Connect
326
fluidsim
In this project we study fluid/structure interactions using a novel particle-based fluid simulation technique.
Erkan Tuzel
Worcester Polytechnic Institute
Physics
Physics
14
OSG Connect
215
cms.org.umd
CMS Connect at University of Maryland
Andris Skuja
University of Maryland
Physics
High Energy Physics
18
CMS Connect
614
NII
The Michigan Neuroimaging initiative aims to enhance and expand neuroimaging research at the University of Michigan and to encourage collaboration with other neuroimaging researchers and researchers in other fields who can contribute innovative methods, computational resources, or new perspectives that will aid neuroimaging research.
Bennet Fauber
University of Michigan
Neuroimaging
Neuroscience
14
OSG Connect
396
UNLbcrf
The Bioinformatics Core Research Facility at UNL runs several large scale compute projects a year. Our main compute is focused on sequence analysis, de-novo assembly and gene prediction/annotation, secondary structure prediction, peptide-protein docking, and phenotype image analysis. We tend to run projects that deal with species critical for agriculture, both crops and livestock, but also with human-virus or food-gut microbiome interactions.
Jean-Jack M. Riethoven
University of Nebraska-Lincoln
Center for Biotechnology
Bioinformatics
14
OSG Connect
597
CUAnschutz_JuarezColunga
Comparison of Random Survival Forests and Joint Modelling for a Time to Event Outcome: a Simulation Study.
Elizabeth Juarez Colunga
University of Colorado Anschutz Medical Campus
Biostatistics and Informatics
Biostatistics
14
OSG Connect
271
atlas.org.tufts
ATLAS Connect team for Tufts University
Robert William Gardner Jr
Tufts University
Physics
High Energy Physics
16
ATLAS Connect
349
DataTrieste
CODATA/RDA Summer School on Research Data Science
Rob Quick
International Center for Theoretical Physics
Education
Multi-Science Community
30
OSG
2097859602
NCSU_Gray
Map and characterize global change, and to understand the consequences of these changes for the Earth system and society. Anthropogenic changes to vegetation (e.g. cropping systems, deforestation, etc.) are of particular interest. Example research questions include: How can we feed a growing population without running out of water? Have tropical deforestation mitigation policies been effective? How is vegetation phenology changing in response to a changing climate?
Josh Gray
North Carolina State University
Center for Geospatial Analytics
Geosciences
322524050
KentState_Thomas
Exploring OSG for local access point and compute element
Philip Thomas
Kent State University
Research Support Services
Computer Science
14
OSG Connect
218
cms.org.neu
CMS Connect at Northeastern University
Emanuela Barbaris
Northeastern University
Physics
High Energy Physics
18
CMS Connect
818249353
CMU_Romagnoli
Deep Reinforcement Learning (RL) for Secure Control of UAVs via Software Rejuvenation
Raffaele Romagnoli
Carnegie-Mellon University
Electrical and computer engineering
Electrical Engineering
14
OSG Connect
724
TG-TRA160027
Indiana University Staff Allocation
Therese Miller
Indiana University
Information Technology
Training
13
OSG-XSEDE
305
NSNM
This model uses Matlab parallel programming to predict noise sensitive neuronal model.
Vadim Apalkov
Georgia State University
Department of Physics and Astronomy
Physics
14
OSG Connect
838207560
UCSD_George
We develop rodent models of addiction, test addiction-like behaviors, neuroadaptations, and novel treatment approaches Applying machine learning and causal inference methods to the analysis of biomedical data.
Olivier George
University of California, San Diego
Psychiatry
Health Sciences
792
GWU_Orti
Evolutionary biology of fishes. Application of genome-wide exon markers to infer fish phylogenies, based on target capture approaches and next-gen sequencing.
Guillermo Orti
George Washington University
Department of Biological Sciences
Life Sciences. Other Sciences
14
OSG Connect
1773809937
Yale_DeMartini
Numerical simulations of the (1+1)D abelian Higgs theory on the lattice focusing on the computation of the sphaleron rate at finite temperatures and potential connections between confinement and entanglement entropy.
Dallas DeMartini
Yale University
Department of Physics
Nuclear Physics
675
ASU_EvolutionMedicineIT
Project for Center for Evolution and Medicine IT staff
Kenneth Buetow
Arizona State University
Center for Evolution and Medicine
Biological Sciences
14
OSG Connect
373
cms-org-cern
CMS Connect group for CERN
Achille Petrilli
CERN
Physics
Particle Physics
18
CMS Connect
798745333
JLAB-TEST
Jefferson Lab's test experiment
Kurt Strosahl
Jefferson Lab
Physics
Nuclear Physics
99
JLab
97362231
FSU_RCC
The Research Computing Center at Florida State University enables research and education by maintaining a diverse campus cyberinfrastructure
Paul van der Mark
Florida State University
Research Computing Center
Research Computing
14
OSG Connect
662
COVID19_UNL_Weitzel
Testing of Folding at Home on the Open Science Grid, for COVID-19; https://foldingathome.org/covid19/
Derek Weitzel
University of Nebraska-Lincoln
Computer Science and Engineering
Computer Science
14
OSG Connect
196
cms.org.ua
CMS Connect at University of Alabama
Conor Henderson
University of Alabama
Physics
High Energy Physics
18
CMS Connect
650
NMSU_staff
NMSU staff experimenting with OSG
Strahinja Trecakov
New Mexico State University
ICT Cyber Infrastructure Architect Team
Computer Science
14
OSG Connect
1714759050
IAState_Iadecola
Structure and nonequilibrium dynamics of disordered quantum many-body systems.
Thomas Iadecola
Iowa State University
Physics and Astronomy
Physics
14
OSG Connect
428
Biomim
The project involves studies of substrate binding, electron and proton transport pathways and substrate release in enzymes that can catalyze the synthesis of fuels in photoelectrochemical cells. The insights obtained will guide the design of small molecule electrocatalysts in collaboration with experimentalists.
Puja Goyal
State University of New York at Binghamton
Chemistry
Chemistry
14
OSG Connect
477
LArSoft
The Liquid Argon Software (LArSoft) Collaboration develops and supports a shared base of physics software across Liquid Argon (LAr) Time Projection Chamber (TPC) experiments.
Erica Snider
Fermilab
Scientific Computing Division
High Energy Physics
9
Fermilab
730
UWMadison_Kaplan
Bayesian Methods for Education Research
David Kaplan
University of Wisconsin-Madison
Educational Psychology
Education
14
OSG Connect
1329691806
KSU_Comer
We use molecular simulation to better understand biological and synthetic nanoscale systems and interactions between them.
Jeff Comer
Kansas State University
Department of Anatomy and Physiology
Health Sciences
14
OSG Connect
160
TG-TRA130011
This allocation will be used to support the use of high performance computing at Indiana University of Pennsylvania. This allocation is a gateway for faculty and students at IUP to gain experience and start using XSEDE resources to further their education and research objectives. This is the Campus Champion allocation request for IUP.
John Chrispell
Indiana University of Pennsylvania
Mathematics
Other
13
OSG-XSEDE
499
HCBData
The project aims to achieve explainable machine learning (ML) through the integration of structured semantic data with the inputs, outputs and hidden layers of deep learning systems. The proliferation of explicitly structured semantic data has occurred in parallel with the emergence of powerful ML algorithms, particularly deep neural networks (DNNs), whose internal layers encode information implicitly. This research attempts to bridge the gap between explicit, easy-to-understand semantic information and implicit, difficult-to-understand features of a deep learning system to achieve transparency and trust in an algorithm's reasoning across multiple layers.
Brad Minnery
Wright State Research Institute
Wright State Research Institute
Computer and Information Science and Engineering
14
OSG Connect
504
sweeps
Running simulations using parameters sampled from large ranges
Murat Acar
Yale University
Molecular Cellular and Developmental Biology
Bioinformatics
14
OSG Connect
397336158
UMontana_Wheeler
Develop software for computational genomics and drug discovery, and apply that software at scale – http://wheelerlab.org
Travis Wheeler
University of Montana
Computer Science department
Biological and Biomedical Sciences
14
OSG Connect
154
TG-AST140088
The IceCube Neutrino Observatory is responsible for providing the IceCube collaboration with Monte Carlo data including cosmic-ray shower simulations and simulation of the IceCube detector response. These simulations are used for studying the systematics of our detector and performance of future geometries. In addition, a large volume of background cosmic ray simulation is needed in order to optimize data analyses.
A key component of simulating the IceCube detector is the correct modeling of the optical properties of the Antarctic ice which requires a lot of computation and has been adapted to run on GPUs.
The IceProd framework is a software package developed for IceCube with the goal of managing productions across distributed systems and pooling together isolated computing resources that are scattered throughout the Collaboration. It consists of a central database hosted at University of Wisconsin-Madison and a set of daemons that are responsible for management of grid jobs as and data handling through the use of existing grid technology and network protocols. The IceCube Monte Carlo production is configured as a distributed workflow DAG that utilizes both CPU and GPU resources for various portions of the simulation chain. The intent is to utilize the Keeneland cluster in Georgia Tech to run GPU tasks and OSG for general CPU tasks through XSEDE. Intermediate files can be stored on a GridFTP server and are typically kept until the individual DAG completes. For a large production run, a typical storage requirement might be on the order of 5 TB.
The IceCube collaboration would like to request an initial allocation of 100,000 SU’s. This allocation will be used to produce and reconstruct Monte Carlo simulations for the IC86 in-ice detectors as well as the IT81 surface detector.
Francis Halzen
University of Wisconsin-Madison
Physics
High Energy Physics
13
OSG-XSEDE
726
BaylorCM_Hirschi
Running mRNA processing pipeline
Kendal Hirschi
Baylor College of Medicine
Molecular and Human Genetics
Biological Sciences
14
OSG Connect
492
DES
Project entry corresponding to the Dark Energy Survey (DES) VO.
Nikolay Kuropatkin
Fermilab
N/A
Astrophysics
9
Fermilab
501
Argoneut
Project entry corresponding to the Argoneut VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
737
TG-MAT200005
Computer simulations of polymer grafted gold nanopores
Elena Dormidontova
University of Connecticut
Institute of Materials Science
Materials Engineering
13
OSG-XSEDE
256
atlas.org.latech
ATLAS Connect team for Louisiana Tech University
Robert William Gardner Jr
Louisiana Tech University
Physics
High Energy Physics
16
ATLAS Connect
321
TG-DMS150022
This research project will focus on using high performance computing for accelerating the numerical methods for modeling the flows of viscoelastic liquids. The computational schemes developed for studying viscoelastic flows are based on an adaptive finite-volume discretization of the Navier-Stokes equations combined with various constitutive laws for viscoelastic liquids. The numerical method is based on a volume of fluid algorithm for tracking the interface, in case of the presence of a second phase. The numerical framework has parallel support using the MPI library, dynamic load-balancing, and parallel offline visualization. The parallel performance of the code will be tested and improved upon. Adaptivity combined with parallelization are essential components of the numerical framework, since transient computations of viscoelastic flows are often very intensive (due to small timestep and high mesh resolution required to resolve high stress regions) and therefore require a large computational resources.
Shahriar Afkhami
New Jersey Institute of Technology
Mathematical Science
Mathematical Sciences
13
OSG-XSEDE
719
CUNYBrooklyn_Juszczak
Mapping molecular level electron density in cation-aromatic pi electron interactions
Laura Juszczak
CUNY Brooklyn College
Chemistry
Chemistry
14
OSG Connect
1411631898
UConn_Le
Methods for ultrafast molecular structure imaging with ultrashort intense laser pulses
Thu Le
University of Connecticut
Physics
Physics
14
OSG Connect
236
cms.org.upr
CMS Connect at University of Puerto Rico
Malik Sudhir
University of Puerto Rico
Physics
High Energy Physics
18
CMS Connect
107
velev
Electronic structure of solids. Electron and spin transport in nanoscale devices.
Julian Velev
University of Puerto Rico
Physics
Computational Condensed Matter Physics
14
OSG Connect
672
TG-DMR190101
1D Nanoconfined Helium: A Versatile Platform for Exploring Luttinger Liquid Physics
Adrian Del Maestro
University of Vermont
Physics
Condensed Matter Physics
13
OSG-XSEDE
73
TG-TRA120041
campus Champion at GWU
Hanning Chen
George Washington University
Chemistry
Computer and Information Science and Engineering
13
OSG-XSEDE
1641205376
NorthwesternMed_Yadav
Monte Carlo simulations of the Boltzmann radiation transport equation to investigate radiation absorbed dose delivered from megavoltage linear accelerators.
Poonam Yadav
Northwestern Medicine
Department of Radiation Oncology
Physics
695
Bucknell_IT
Group for Bucknell Research IT staff to test-drive OSG job submissions
Jeremy Dreese
Bucknell University
Engineering
Computer Sciences
14
OSG Connect
351
TG-PHY160031
We request computing time on Stampede to perform air shower simulations for the VERITAS air Cherenkov gamma-ray telescope. The new set replaces an existing 5 year old set of shower simulations. Air shower simulations are essential to understand the instrument response of VERITAS and needed in the analysis of VERITAS data. The proposed new set of simulations will allow the VERITAS Collaboration to extend the usable energy range of the VERITAS instrument beyond 10 TeV and significantly reduce systematic uncertainties at all energies.
Nepomuk Otte
Georgia Institute of Technology
School of Physics & Center for Relativistic Astrophysics
Mathematical Sciences
13
OSG-XSEDE
378
nicesims
The Nice Model, is an evolutionary model for the outer Solar System which has explained many puzzling observed qualities of the Solar System. As the newly formed planets cleared debris from the young Solar System, Saturn, Uranus, and Neptune tended to scatter objects inward, while Jupiter ejected these planetesimals out of the Solar System. To conserve angular momentum through this process, Jupiter slowly migrates inward while the other giant planets move outward. When Jupiter and Saturn cross a period of orbital resonance, the entire Solar System experiences a massive instability. We will run simulations to probe the affect of such an instability on an evolving system of inner planets.
Nathan Kaib
University of Oklahoma
Physics and Astronomy
Physics and astronomy
14
OSG Connect
57
DeerDisease
I have created an individual-based computer model simulating disease spread in deer populations. The population in the model is represented by deer agents that all follow rules and behaviors. I am using Repast Simphony 1.0 and the code is written in java.
Lene Jung Kjaer
Southern Illinois University
Department of Zoology
Biological Sciences
30
OSG
1484988684
Rice_Li
We do research on experimental nuclear and particle physics at the LHC. Our main purpose of using OSG is to perform phenomenological model simulations to compare with and understand the experimental data. https://lilab.rice.edu/
Wei Li
Rice University
Physics and Astronomy Department
Physics
394
NCOppSchool
Studying the effects of the North Carolina Opportunity Scholarship using a discrete choice model. The estimation recovers utility parameters for school choice using school enrollments.
Michael Dinerstein
The University of Chicago
Economics
Economics
14
OSG Connect
1319196150
TG-TRA220014
This Campus Champions allocation will primarily be used to allow USDA-ARS SCINet (https://scinet.usda.gov/) users to evaluate Jetstream as a possible alternative to public cloud (AWS, Azure) resources, which can be administratively difficult to obtain; as well as evaluate resources (e.g., newer GPU models) that are unavailable on SCINet HPC clusters.
Nathan Weeks
USDA Agricultural Research Service
Corn Insects and Crop Genetics Research Unit
Training
14
OSG Connect
2110663488
UTEP_DeBlasio
Our group studies how to improve science by automating and optimizing the tools used by domain scientists. We do this primarily by making input specific parameter value choices which help to reduce false information introduced by using less than ideal (or default) parameter choice. The focus of the work performed here will be on data acquisition for the machine learning processes needed to further develop these methods used for making such choices for multiple sequence alignment applications. https://deblasiolab.org/
Dan DeBlasio
University of Texas at El Paso
Department of Computer Science
Computer and Information Sciences
14
OSG Connect
842
UCHC_Mendes
We follow the Systems Biology approach, where biological phenomena are seen as resulting from the interactions of its constituents. Interpreting these phenomena requires the use of quantitative methods and computation. We work on many aspects of Computational Systems Biology: Development of modelling and simulation software (like COPASI) Construction of large-scale cellular models (digital organisms) Parameter estimation and sensitivity analysis Standards for systems biology Multiscale modelling and simulation Reverse-engineering biological networks (top-down modelling) Enzyme kinetics for model construction (bottom-up modelling) We are also involved in modeling biological phenomena: The network of iron absorption, metabolism and signalling in mammals Dynamics of eukaryotic protein synthesis Mixed species Candida albicans-bacterial biofilm formation
Pedro Mendes
University of Connecticut Health Center
Department of Cell Biology
Biological Sciences
14
OSG Connect
738
Vanderbilt_Gabella
Numerical Relativity simulations of astronomical gravitational wave progenitor systems
William Gabella
Vanderbilt University
Physics
Physics
14
OSG Connect
285974151
RutgersOARC
Rutgers Office of Advanced Research Computing
Bala Desinghu
Rutgers, The State University of New Jersey
OARC
Computer Science
14
OSG Connect
474
psychosisfmri
This project will make use of fMRI data of psychotic patients in order to parse heterogeneity in functional activity across multiple diagnosis. The need for computing power results from the need to preprocess the fMRI, from which we want to obtain a region level connectivity matrix for each of the approximately 1200 subjects that will be analyzed.
De Sa Nunes Correia Diogo
Northeastern University
College of Science
Neuroscience
14
OSG Connect
267
atlas.org.sc
ATLAS Connect team for University of South Carolina
Robert William Gardner Jr
University of South Carolina
Physics
High Energy Physics
16
ATLAS Connect
518
ORISSWarp
Using Warp to model ORISS to investigate the effects of intense space charge on the charged particle optics
Steve Lund
Facility for Rare Isotopes Beams (FRIB)
Accelerator Systems
Nuclear Physics
14
OSG Connect
550
TG-PHY180035
Calibrating JETSCAPE 1.0 Understanding jets in a Quark Gluon Plasma
Abhijit Majumder
Wayne State University
Physics and Astronomy
Nuclear Physics
13
OSG-XSEDE
1707378612
NOAA_Fisch
My research aims to improve population models of fisheries resources so as to better facilitate seafood sustainability and our understanding of marine and freshwater populations. This involves the development of highly-parameterized non linear models requiring numerical solutions and numerical integration.
Nicholas Fisch
National Oceanic and Atmospheric Administration
National Marine Fisheries Service
Natural Resources and Conservation
798
GATech_Ross
Facilitation for GATech H. Milton Stewart School of Industrial and Systems Engineering
Kelly Ross
Georgia Institute of Technology
School of Industrial and Systems Engineering
Industrial and Manufacturing Engineering
14
OSG Connect
831
Illinois_Vieira
The Observational Cosmology Laboratory (ObsCos) work explores the early universe through the echos of the big bang, known as the Cosmic Microwave Background (CMB). The ObsCos lab is developing cryogenic optics for next-generation CMB experiments. This R&D exposes students to clean-room tasks, software simulation, electronics, data acquisition and involvement in a large scale scientific research project.
Joaquin Vieira
University of Illinois Urbana-Champaign
Astronomy
Astronomy
14
OSG Connect
570
WSU_3DHydro
(3+1)D Dynamical modeling of relativistic heavy-ion nuclear behavior
Chun Shen
Wayne State University
Department of Physics and Astronomy
Nuclear Physics
14
OSG Connect
359
SO10GU
searching for different realistic SO(10) GUT models that are able to reproduce the experimentally observed fermion masses and mixings
shaikh saad
Oklahoma State University
Physics
High Energy Physics
14
OSG Connect
525
MLResearch
Image Reconstruction of Satellites using Machine Learning using MATLAB.
Ashish Tiwari
Georgia State University
Computer Science
Computer Science
14
OSG Connect
2105275840
UWMadison_Weigel
Animal breeding and Genomics
Kent Weigel
University of Wisconsin-Madison
Animal and Dairy Sciences
Genomics
68
aprime
DarkLight experiment planned to run at Jefferson LAB in the upcoming years will search for a massive photon possibly produced in interaction of an electron with electric filed of a proton.
Monte-Carlo simulations are needed design and optimize the Darklight experiment. The initial OSG-Connect resources of few CPU years will be sufficient. The simulation will use CERN libraries, namely: Geant4.10, root5.34, compiled on Scientific Linux 6.5.
Jan Balewski
Massachusetts Institute of Technology
LNS
Nuclear Physics
14
OSG Connect
1819838320
MSU_Kerzendorf
Astronomy simulations for machine learning
Wolfgang Kerzendorf
Michigan State University
Department of Physics and Astronomy
Astronomy
14
OSG Connect
185
mab
Developing new policies for the (classical) Multi-Armed Bandit problem.
Vivek Farias
Massachusetts Institute of Technology
Sloan School of Management
Information Theory
14
OSG Connect
863451074
CSUN_Katz
Large scale searches for binary sequences with identical autocorrelation spectra (https://arxiv.org/abs/2308.07467).
Daniel Katz
California State University, Northridge
Department of Mathematics
Mathematics
44
TG-BCS110002
The George E. Brown Jr. Network for Earthquake Engineering Simulation (NEES) project is a National Science Foundation funded project operating a shared national network of civil engineering experimental facilities that seeks to develop effective ways of mitigating earthquake damage and loss of life using improved designs, materials, construction techniques, and monitoring methods. Safer buildings and civil infrastructure are needed to reduce damage and loss from earthquakes and tsunamis. Preparing for and protecting against these threats makes American communities more resilient to future disasters. To support research in the Civil Engineering community that seeks to address these problems, NEES operates 14 distributed research equipment sites across the United States. The objectives of NEES are to: develop a national and multi-user research infrastructure to enable research and innovation in earthquake and tsunami loss reduction; create an educated workforce in hazard mitigation; and conduct broader outreach and lifelong learning activities. Experimental capabilities at the 14 NEES sites include large-scale shake tables, a tsunami wave basin, large-scale testing facilities, centrifuges, field and mobile facilities, a large-scale displacement facility, and cyberinfrastructure capabilities. NEEScomm, led by Purdue University, connects the 14 NEES research equipment sites and the earthquake engineering community with a powerful information technology infrastructure and a commitment to education, outreach and training related to earthquake engineering. The center facilitates community collaboration and discovery by working to advance research based on experimentation and computational simulations of the performance of buildings, bridges, utility systems, coastal regions, and geomaterials during seismic events. In conjunction with supporting research, NEES seeks to disseminate results through education, outreach, and training to reduce the devastation and loss of human life from earthquakes and tsunamis. Through a cooperative agreement with the National Science Foundation, the NEEScomm center is charged with leading and managing the operations of this national resource, and enabling collaboration between the 14 NEES research equipment sites and the earthquake engineering community through groundbreaking cyberinfrastructure, education and outreach efforts. NEES provides access to a variety of analysis and simulation tools for the NEES community, which includes OpenSees, OpenFresco, UI-SimCor, RDV, and Data Turbine. A groundbreaking cyberinfrastructure, the NEEShub (http://www.nees.org), connects researchers, practitioners, and the greater civil engineering community with the 14 research labs. NEEShub features the NEES Project Warehouse, which archives data gathered in all NEES experiments, along with a rich set of tools for data management, data viewing, and computational simulation. Most projects include, in addition to physical experimentation, a substantial computational component for comparison with and validation of the physical tests. As part of the Information Technology services provided to the NEES community, NEEScomm is expected to provide production quality cyberinfrastructure that is reliable and relevant to the needs of the NEES community, and to provide facilitated access to and use of campus and/or national computing resources. This proposal seeks to continue and extend the support for computational experiments in the NEES research community.
Thomas
Purdue University
Computer & Information Technology
Biological and Critical Systems
13
OSG-XSEDE
444
mortality
his project is about the mortality of developed countries in Human Fertility Database.
Shripad Tuljapurkar
Stanford University
Biology
Biological Sciences
14
OSG Connect
11
BNLPET
Positron Emission Tomography (PET) at BNL: Develop the efficient and easily parallelizable 3D image reconstruction algorithms for Positron Emission Tomography detectors developed by the BNL PET group. Use OSG XSEDE resources for reconstructing the images obtained by the group while doing a biomedical and biochemistry research. http://www.bnl.gov/pet/ .
Martin Purschke
Brookhaven National Laboratory
Physics Department
Medical Sciences
30
OSG
336
IRRI
Collaboration with the Rice3k IRRI project
Mats Rynge
University of Southern California
ISI
Bioinformatics
9
ISI
299
CGS
Project Name: grian growth simulation
Short Project Name: GGS
Field of Science: Materials Science
Field of Science (if Other):
PI Name: Panthea Sepehrband
PI Email: psepehrband@scu.edu
PI Organization: Santa Clara Univeristy
PI Department: Mechanical Engineering
Join Date:
Sponsor:
OSG Sponsor Contact:
Project Contact: Panthea Sepehrband
Project Contact Email: psepehrband@scu.edu
Telephone Number: 4088338665
Project Description: Simulation of grain growth using the LAMMPS package.
Panthea Sepehrband
Santa Clara University
Mechanical Engineering
Materials Science
14
OSG Connect
771
XSEDE_XCI
The mission of the XSEDE Cyberinfrastructure Integration (XCI) team is to integrate, adapt, and disseminate software tools and related services across the national CI community enabling the US research community to do its work better and more easily than before – making it easier for administrators and users of campus-based cyberinfrastructure systems to make use of tools created by XSEDE for local benefit, and expand upon XSEDE's effort to enable the creation of an integrated national cyberinfrastructure. XCI is using OSG resources to learn how OSG tools and services work, and to explore potential areas of collaborations. This includes but is not limited to OSG Connect, HTCondor, CVMFS, and identity and access management services. https://www.xsede.org/ecosystem/ci-integration
John-Paul Navarro
Argonne National Lab
XSEDE Cyberinfrastructure Integration (XCI)
Computer Sciences
14
OSG Connect
531
eht
The Event Horizon Telescope (EHT) is an international collaboration aiming to capture the first image of a black hole by creating a virtual Earth-sized telescope.
Chi-Kwan Chan
University of Arizona
Astronomy
Astronomy
14
OSG Connect
304
z2dqmc
We study Z2 lattice gauge theory coupled to fermonic matter fields. The problem can be studied using sign problem free quantum Monte Carlo allowing a numerically unbiased computation.
Snir Gazit
University of California, Berkeley
Physics
Physics
14
OSG Connect
465
ReABuncherRing
Design of a pre-RFQ buncher ring for ReA at FRIB
Phil Duxbury
Michigan State University
Physics and Astronomy
Physics and astronomy
14
OSG Connect
193
Paniceae-trans
Processing of Transcriptome data from many species across the grass tribe Paniceae
Jacob Washburn
University of Missouri
Biological Sciences
Evolutionary Sciences
14
OSG Connect
732
UCSD_Arovas
Entanglement in boundary driven systems
Daniel Arovas
University of California, San Diego
Physics
Physics
14
OSG Connect
120
TAMUpheno
The Large Hadron Collider (LHC) experiments have successfully discovered the last missing piece of the standard model (SM)—the elusive Higgs boson. However, no sign of any physics beyond the SM has been observed yet. Although the standard model has been extremely effective, many unsolved questions still remain.
The focus of our group is to study models of physics beyond the SM, which tries solve the aforementioned unsolved questions, and explore their possible signatures, at LHC experiments predominately. These models include Supersymmetric models, Grand Unified Theories, Left-Right Symmetric models and various Dark Matter models.
LHC is going through an upgrade now and it will start functioning again next year with increased energy. We are pursuing a number of projects trying to predict the possible signature of new physics, pertaining to various models described above, in upcoming LHC experiments. Owing to these we need sufficient comuting power and intend to run collider simulators including MadGraph, Pythia, PGS, Delphes etc.
Bhaskar Dutta
Texas A&M University
Department of Physics & Astronomy
High Energy Physics
14
OSG Connect
816
UWMadison_Keller
Studying the genetic regulation and production of fungal secondary metabolites.
Nancy Keller
University of Wisconsin-Madison
Medical Microbiology and Immunology
Biological Sciences
14
OSG Connect
127
BNL-PHENIX
Running HEP/NP Monte Carlo simulations for the collaboration of the PHENIX detector at Relativistic Heavy Ion Collider (RHIC) at BNL.
Matthew Snowball
Brookhaven National Laboratory
Physics Department
Nuclear Physics
30
OSG
322523477
RIT_Tu
Study on Solid State Battery Cathode Optimization
Howard Tu
Rochester Institute of Technology
Mechanical Engineering
Mechanical Engineering
328
CpDarkMatterSimulation
Generate a grid of Monte Carlo samples to be used in collider-based searches for dark matter
Christoph Paus
Massachusetts Institute of Technology
Physics
High Energy Physics
30
OSG
846
Rice_Fox
Consumer behavior prediction analysis
Jeremy Fox
Rice University
Economics
Economics
14
OSG Connect
688
Rowan_Nguyen
Machine Learning and Error-Correcting Output Codes (ECOC)
Hieu Nguyen
Rowan University
Mathematics
Computer Sciences
14
OSG Connect
84
TG-MCB140160
Description: RNA aptamers are small oligonucleotide molecules (~100 nucleotides) whose composition and resulting folded structure enable them to bind with high affinity and high selectivity to specific target ligands and therefore hold great promise as potential therapeutic drugs. The first aptamer to receive FDA approval was pegaptanib (Macugen), which is a treatment for wet age-related macular degeneration, a degenerative disease of the macula of the eye that leads to the loss of central vision. The pegaptanib aptamer acts by binding to and inhibiting the action of an isoform of vascular endothelial growth factor (VEGF), arresting degeneration. Functional aptamers are selected from a large, randomized initial library in a process known as SELEX (systematic evolution of ligands by exponential enrichment). This is an iterative process involving numerous rounds of binding, elution, and amplification against a specific target substrate. During each iteration - or round of selection - we enrich for the species with the highest binding affinity to the target. After multiple rounds, we ideally have an enriched aptamer library suitable for subsequent investigation. Modern techniques employ massively parallel sequencing, enabling the generation of large libraries (~10^{6} sequences) in a matter of hours for each round of selection. As RNA is single-stranded, the covariance model (CM) approach (Eddy, SR, Durbin, R (1994). RNA sequence analysis using covariance models. Nucleic Acids Res., 22, 11:2079-88) are ideal for representing motifs in their secondary structures, allowing us to discover patterns within functional aptamer populations following each round. CMs have been implemented in 'Infernal' (http://infernal.janelia.org) a program that infers RNA alignments based on RNA sequence and structure. Calibrating a single CM in Infernal however can take several hours and is a significant performance bottleneck for our work. However, as each CM calculation is itself independently determined and requires defined pr!
ocessing
and memory resources, their computation in parallel using the Open Science Grid offers a potential solution to this problem. Using part of a Campus Champion award to our institution, we have prototyped such a solution by making use of the Simple API for Grid Applications (SAGA) to interface with OSG and manage job submissions and file transfers. When run in parallel, our results showed a significant speed up, constrained by typical latencies and QoS associated with nominal OSG usage. This prior study demonstrated the feasibility of using SAGA and the OSG to support the parallelization of CM analysis of such large scale sequence based aptamer libraries, and forms the basis of this startup allocation request to further constrain workflow productivity and support the PhD research of Mr. Kevin Shieh.
David Rhee
Albert Einstein College of Medicine
Genetics
Molecular and Structural Biosciences
13
OSG-XSEDE
248237660
Syracuse_Nitz
Looking for sub-solar mass neutron stars.
Alex Nitz
Syracuse University
Physics
Astronomy and Astrophysics
381
UNH-IMD
We are interested in developing new quantum chemistry methods and chemical structure optimization algorithms to design green heterogeneous catalysts.
Dequan Xiao
University of New Haven
Chemistry
Chemistry
14
OSG Connect
27
UChicago-RCC
University of Chicago Research Computing Center (http://rcc.uchicago.edu) supporting the computational requirements of multiple science domains.
Birali Runesha
University of Chicago
Research Computing Center
Training
14
OSG Connect
1205313563
Stanford_Gilula
Gather statistics about the evolution and final conditions of various random initial configurations under certain symmetries in two-dimensional cellular automaton, mainly Conway's Game of Life
Maxim Gilula
Stanford University
Mathematics
Mathematics
14
OSG Connect
812
Columbia_Gibson
fMRI Data Processing
Lisa Gibson
Columbia University
Psychology
Health
14
OSG Connect
174
ProbTracx
Graph theory analyses would be investigated on weighted undirected matrices based on the probability of white matter connectivity between 26 regions comprising both cortical and subcortical structures on children with epilepsy with and without anxiety disorders. This project aims at investigating if there are fundamental differences in structural connectivity in children with idiopathic epilepsy with and without anxiety comorbidity. The neuropsychological implications of potential differences between groups would also be investigated.
Dr. Bruce P. Hermann
University of Wisconsin-Madison
Department of Neurology
Neuroscience
14
OSG Connect
648
Arizona_Paschalidis
Systematic Testing of Neutron Star Universal Relations
Vasileios Paschalidis
University of Arizona
Physics
Physics
14
OSG Connect
3
SNOplus
SNO+ is a multi-purpose liquid scintillator detector with a primary goal of studying neutrino-less double beta decay in Tellurium-130, and is also capable of measurements involving solar neutrinos, reactor antineutrinos and geoneutrinos, supernovae, certain nucleon decay modes. Data collected by the detector are moved to (UK and Canadian) grid storage, where automated processing occurs. The large number of simulated data sets required for statistical analyses are also produced on grid resources. The total combined size of the data and simulations is expected to be on the order of 100 TB, which makes transfer, storage, and processing (i.e. running custom ROOT code) intractable on local resources available at collaborating US institutions. Hence, access to grid storage and processing is imperative for the analysis of the SNO+ data by US Collaborators.
Joshua R Klein
University of Pennsylvania
Physics and Astronomy
High Energy Physics
30
OSG
124
NapusGenome
Assembling the genome of a number of plant lines, and conducting RNASeq studies for the development of a transcriptome and differential expression analysis.
Joel Bader
Johns Hopkins University
Department of Biomedical Engineering
Biological Sciences
14
OSG Connect
713548387
TG-CIE160039
Campus Champions at Carnegie Mellon University
Franz Franchetti
Carnegie-Mellon University
ECE
Engineering Systems
14
OSG Connect
1892807723
UALR_Goodarzi
focus on drug discovery for infection and cancer, leveraging computational methods. Specifically, I utilize computation for analyzing protein-protein interactions, protein-ligand interactions, and multivariate analysis. This approach aids in identifying potential drug targets and understanding molecular mechanisms. Overall, my work integrates computational tools to advance drug discovery efforts against infection and cancer.
Mohammad Goodarzi
University of Arkansas at Little Rock
Chemistry
Biochemistry
896812233
Auburn_Hauck
Experimental infections with avian reovirus and co-infections with other micro-organisms. We analyze bioinformatic data pertaining to microbiome, gene expression, metagenome and transcriptome obtained from these experiments.
Ruediger Hauck
Auburn University
Pathobiology
Agricultural Sciences specifically Poultry Science
14
OSG Connect
637
GSU_Wang
Measuring Corporate Cybercrime Risk
David Maimon
Georgia State University
Institute for Insight
Business
14
OSG Connect
85
NEESTools
Earthquake Engineering is moving towards performance based
engineering. Performance based engineering will potentially
require and exponentially increase the amount of computation
required of engineers as engineers move to incorporate risk and
uncertainty associated with hazard, modeling, cost, material,
etc. into the simulations. Currently those in research mostly are
using the OpenSees (http://opensees.berkeley.edu) application to
perform these calculations. This project aims at providing these
researchers with access to current versions of OpenSees by
utilizing resources to build the application on OSG resources.
Frank McKenna
University of California, Berkeley
Civil Engineering
Civil Engineering
30
OSG
460
TelescopeArray
Telescope Array (TA) is the largest cosmic ray detector in the Northern hemisphere, which is located in Millard county, Utah. TA studies cosmic ray energy spectrum, mass composition, and arrival directions in the energy range from 4 PeV to 100 EeV and above. The address of the projects' website is http://www.telescopearray.org.
Gordon Thomson
University of Utah
Physics
Astrophysics
14
OSG Connect
823
USheffield_DUNE
The Deep Underground Neutrino Experiment is an international flagship experiment to unlock the mysteries of neutrinos.
Stefan Söldner-Rembold
University of Sheffield
Physics and Astronomy
Physics
14
OSG Connect
351028049
Etown_Wittmeyer
I am interested in examining experience-dependent neuroplasticity and individual differences in humans as it pertains to learning and memory. In particular, I analyze structural magnetic resonance imaging (sMRI) data from various neuroimaging data-sharing platforms to explore changes in gray matter across learning and/or correlate learning performance with various cognitive and demographic factors.
Jennifer Legault Wittmeyer
Elizabethtown College
Psychology
Psychology and Life Sciences
14
OSG Connect
502
SBND
Project entry corresponding to the SBND VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
123
SBND
145
HypergraphDegreeSeq
A degree sequence of a hypergraph is a list of numbers that gives the total number of edges each vertex is in and multiple hypergraphs can have the same degree sequence. I'm trying to determine a minimal set of moves that connects all of the realizations. I need to use parallel programming as there are many degree sequences to investigate.
Sarah Lynne Behrens
University of Nebraska-Lincoln
Mathematics
Mathematical Sciences
67
HCC
540678325
TG-MCB160020
Hands on Training on Robust Molecular Simulations Introduces students to the exciting areas in Computational Biophysics, drug design, bioinformatics and potentially other computing intensive fields
Rejwan Ali
Icahn School of Medicine at Mount Sinai
Neurology
Biological and Biomedical Sciences
14
OSG Connect
473
Dissertation
This study involves the use of Monte Carlo simulation methods to test the use of mixture models to improve the estimation of a latent ability.
Ann Arthur
University of Nebraska-Lincoln
Educational Psychology
Educational Psychology
14
OSG Connect
581
PanEn
Parallel Analog Ensemble (PAnEn) is a parallel implementation for the Analog Ensemble (AnEn) technique which generates uncertainty information for a deterministic predictive model.
Guido Cervone
Pennsylvania State University
Geography
Geography
14
OSG Connect
1329542929
OSGUserSchool2022
Group for OSG User School 2022 participants
Tim Cartwright
University of Wisconsin-Madison
Computer Sciences
Research Computing
14
OSG Connect
259
atlas.org.mit
ATLAS Connect team for MIT
Robert William Gardner Jr
Massachusetts Institute of Technology
Physics
High Energy Physics
16
ATLAS Connect
729
UF_Staff
Group for research computing staff at University of Florida
Erik Deumens
University of Florida
Information Technology
Computer Sciences
14
OSG Connect
1673984284
UWMadison_Payseur
Work on understanding the origin of species and the evolution of recombination
Bret Payseur
University of Wisconsin-Madison
Genetics
Genomics
510
cellpainting
We aim to pioneer a new era where images of cells become
powerful, rich, unbiased data sources for comparing cell state. We predict that
doing so will allow rapid and inexpensive interrogation of the impact of genetic
or chemical perturbations on a cell - useful for a variety of important
applications in biology.
In morphological profiling, we construct signatures of genes, chemicals, or
other treatments by measuring the structural changes in treated cells, as
observed under a microscope. Cells are stained with fluorescent dyes that mark
several constituents, producing images from which hundreds of distinct
measurements can be extracted at the single cell level. We will carry out
proof-of-principle computational experiments using morphological profiling in
diverse and significant applications, such as connecting unannotated genes to
known pathways, identifying signatures of disease, predicting a small molecule’s
mechanism of action, enriching chemical libraries for diverse bioactivity, and
identifying new compounds or materials with desired phenotypic effects. Despite
our successes in this field so far, the methods development for morphological
profiling is a wild frontier: novel methods are used but not compared,
integration with other data types (such as transcriptomics) has not !
been explored, and deep learning is not yet leveraged to its potential. We will
continue to push forward the technology development needed in our driving
biological projects. We will make data and code publicly available to catalyze
the field. Ultimately, we aim to develop best practices for the field and create
the foundation for user-friendly, open-source tools to discover and quantify
relationships among genetic or chemical perturbations and disease state, across
a diverse array of biological areas of study and disease areas.
Shantanu Singh
Broad Institute
Imaging Platform
Molecular and Structural Biosciences
14
OSG Connect
509
FDDRCS
The Project entails the estimation of a general equilibrium heterogenous firms dynamic model with default. The Project is related to the paper "Financial Development, Default Rates, and Credit Spreads" (abstract below), at the moment R&R at the Economic Journal.
Alessandro Peri
University of Colorado Boulder
Economics
Economics
14
OSG Connect
656
WCUPA_Ngo
Emulating sensor data collection via the OSG
Linh Ngo
West Chester University of Pennsylvania
Computer Sciences
Computer Science
14
OSG Connect
824
Cincinnati_RCD
Research Technologies staff at the University of Cincinnati
Jane Combs
University of Cincinnati
Advanced Research Computing Center
Computer Sciences
14
OSG Connect
339717243
IIT_Wereszczynski
https://wereszczynskilab.org/research/
Jeff Wereszczynski
Illinois Institute of Technology
Physics
Biological and Biomedical Sciences
14
OSG Connect
92777637
UMissouri_Nada
Running segmentation of 100 subjects through Freesurfer. Comparing the volumetric measurements of the midbrain between the disease group (PS) and control group. PSP is a movement disorder characterized by atrophy of the midbrain. We investigate quantification of the midbrain volume to early predict the disease.
Ayman Nada
University of Missouri
Radiology Department
Medical Sciences
14
OSG Connect
584
KSU_Li
Virtual screening of compound library using AutoDock Vina for the discovery of drug/inhibitor of NTMT1
Ping Li
Kansas State University
Chemistry
Chemistry
14
OSG Connect
367
EmpModNatGas
I study the privately negotiated outcomes of the natural gas leasing market for mineral rights using a one-to-many matching model that allows for the presence of complementary preferences among firms negotiating bundles of land leases.
Ashley Vissing
University of Chicago
Economics
Economics
14
OSG Connect
74
SBGrid
SBGrid work using OSG Connect
Piotr Sliz
Harvard Medical School
Biological Chemistry and Molecular Pharmacology
Biochemistry
14
OSG Connect
50
TG-MCB090174
We propose to use multiple XSEDE resources to study several scientific problems. This work is built on theextensive efforts over the past three years we have carried out within a wide range of computational science,cyberinfrastructure and computer science projects, requiring us to use concurrent multiple resources onXSEDE. Specifically, in this proposal we request 10.04M on Stampede, 2.07M on Kraken, 0.37M on Tres-tles and 0.1M on Blacklight for four distinct projects: (i) Atomisitic simulation of Physiological Systems;Extensible and Scalable middleware and tools for XSEDE and Open Science Grid.This proposal is fundamentally multi-disciplinary and collaborative. Importantly resources being re-quested are part of and supported by multiple federally funded and even International funded projects (inconjunction with NSF). This work is primarily funded by NSF CAREER Award (OCI-1253644; PI Jha), aswell as by NSF Cyber-enabled Discovery and Innovation Award (CHE-1125332; co-PI Jha), NSF-ExTENCIergy Award (ASCR, DE-FG02-12ER26115, PI Jha). A significant grant (ExTASY) as part of the US-UKNSF-EPSRC call in Chemsitry has been awarded at the UK end and is awaiting processing at the US end.
Shantenu Jha
Rutgers, The State University of New Jersey
None Stated
Molecular and Structural Biosciences
13
OSG-XSEDE
100142798
UCSD_Duarte
Machine learning (ML) development for particle physics, primarily for the CMS experiment at the CERN Large Hadron Collider.
Javier Duarte
University of California, San Diego
Department of Physics
High Energy Physics
14
OSG Connect
1204137902
Dearborn_Shawver
AP Research project on 3x+1 conjecture
Kimberly Shawver
Dearborn Center for Math, Science, and Technology
Computer Science
Computer and Information Sciences
14
OSG Connect
1477014382
Duke_Charbonneau
Periodic microphases universally emerge in systems for which short-range inter-particle attraction is frustrated by long-range repulsion. The morphological richness of these phases makes them desirable material targets, but our relatively coarse understanding of even simple models limits our grasp of their assembly. The OSG computing resources will enable us to explore more solutions of the equilibrium phase behavior of a family of similar microscopic microphase formers through specialized Monte Carlo simulations.
Patrick Charbonneau
Duke University
Chemistry
Computational Condensed Matter Physics
642825052
Vanderbilt_Paquet
study the quark-gluon plasma produced in collisions of nuclei. I perform relativistic hydrodynamic simulations of the collisions and study in particular the production of photons in the collisions. This is my Vanderbilt website: https://as.vanderbilt.edu/physics-astronomy/bio/jean-francois-paquet/ This is my professional website: https://j-f-paquet.github.io/
Jean-Francois Paquet
Vanderbilt University
Department of Physics & Astronomy
Physics
158
CHomP
Our group studies dynamical systems using methods from computational topology. A current focus is the study of gene regulatory networks via switching system models and the computation of Conley-Morse databases.
Konstantin Mischaikow
Rutgers, The State University of New Jersey
Mathematics
Mathematical Sciences
14
OSG Connect
372
MMHA
The project aim is to estimate structural parameters of dynamic heterogeneous agent model to investigate the optimal design of monetary and financial policies. In particular, we need to find numerical solutions for stochastic dynamic programming problems with many state variables.
Ikuo Takei
University of Wisconsin-Madison
Economics
Economics
14
OSG Connect
265
atlas.org.ou
ATLAS Connect team for Oklahoma University
Robert William Gardner Jr
Oklahoma University
Physics
High Energy Physics
16
ATLAS Connect
1623471359
Illinois_Petravick
The CMB-S4 project is prototyping processing and data flow on the FABRIC testbed https://portal.fabric-testbed.net/. We are studying the use of HTCondor on FABRIC VM nodes in scenarios where data would arrive over high speed networks.
Donald Petravick
University of Illinois Urbana-Champaign
National Center for Supercomputing Applications (NCSA)
Astronomy
14
OSG Connect
1999163399
UCDavis_Leveau
Study of plant-microbe interactions specifically pertaining to microbes in the phyllosphere (leaf surface)
Johan Leveau
University of California, Davis
Department of Plant Pathology
Biological and Biomedical Sciences
14
OSG Connect
71
TG-DMS120024
This allocation will be used to help MSU users transition from local HPC resources to XEDE resrouces.
Benjamin Ong
Michigan State University
Institute for Cyber Enabled Research
Mathematical Sciences
13
OSG-XSEDE
93
atlas.org.illinois
University of Illinois Urbana/Champaign Tier 3 ATLAS group.
Mark Neubauer
University of Illinois
Physics
High Energy Physics
16
ATLAS Connect
338
TDAstats
Topological data analyses on various datasets
David Meyer
University of California, San Diego
Mathematics
Mathematical Sciences
14
OSG Connect
713
UCR_ITSStaff
Research Computing Staff in Information Technology Solutions (ITS) at University of California, Riverside.
Chuck Forsyth
University of California, Riverside
Information Technology Solutions
Computer and Information Sciences
14
OSG Connect
1752485673
NMSU_Sievert
Theoretical nuclear physics research.
Matthew Sievert
New Mexico State University
Physics
Physics
674839994
UWMadison_Li
Multiscale modeling, computational materials design, mechanics and physics of polymers, and machine learning-accelerated polymer design.
Ying Li
University of Wisconsin-Madison
Mechanical Engineering
Engineering
450
snasim
This is project is to run conditions to determine the social network factors (e.g., structure, size,density) that affect the statistical power for detecting the interaction term of contagion parameter.
Wei Wang
University of Central Florida
Psychology
Educational Psychology
14
OSG Connect
362557967
IIT_Rosa
Generating trajectories in high-dimensional parameter spaces using numerical continuation methods. The software repo is available here: https://github.com/nr-codes/BipedalGaitGeneration.
Nelson Rosa
Illinois Institute of Technology
Mechanical, Materials, and Aerospace Engineering Deptartment
Mechanical Engineering
14
OSG Connect
24
NESCent
NESCent promotes the synthesis of information, concepts and knowledge to address significant, emerging, or novel questions in evolutionary science and its applications. NESCent achieves this by supporting research and education across disciplinary, institutional, geographic, and demographic boundaries.
Fabricia Nascimento
Duke University
NESCent Center
Evolutionary Sciences
14
OSG Connect
361
EDFCHT
The project looks into the use of heteroskedasticity consistent variance-covariance estimators for conducting hypothesis testing. It uses Monte Carlo and bootstrap techniques to find the distribution of t-statistics using heteroskedasticity consistent variance-covariance estimator under normality and nonnormality. Comparison between using different heteroskedasticity consistent estimators are included and possible corrections are proposed and will be examined.
Jianghao Chu
University of California, Riverside
Economics
Economics
14
OSG Connect
139
ProtEvol
How large a role does history play in evolution? Do later events depend critically on specific earlier events, or do all events occur more or less independently? If a change occurs early in evolution, does it become easier or harder to revert the change as time proceeds? We intend to explore these ideas in the context of protein evolution, by simulating sequence evolution under purifying selection and then systematically permuting the order of amino-acid substitutions.
Premal Shah
University of Pennsylvania
Biology
Evolutionary Sciences
14
OSG Connect
736
UCSF_Manglik
G protein coupled receptor (GPCR) modeling
Aashish Manglik
University of California, San Francisco
Pharmaceutical Chemistry
Biological and Biomedical Sciences
14
OSG Connect
391
duke-staff
campus project
Tom Milledge
Duke University
IT
Community Grid
15
Duke
541
LyCfesc
Lyman continuum escape fraction. Monte Carlo simulations of galaxy light absorption.
Rogier Windhorst
Arizona State University
Astrophysics
14
OSG Connect
557024568
Emory_Chavez
Simulate Monte Carlo experiments of social interaction models to assess the small sample performance of the estimator.
David Jacho-Chavez
Emory University
Department of Economics
Economics
14
OSG Connect
606
Mines_Leach
Nuclear Two-Photon Decay with GRIFFIN
Kyle Leach
Colorado School of Mines
Physics
Physics
14
OSG Connect
205
cms.org.fiu
CMS Connect at Florida International University
Pete Markowitz
Florida International University
Physics
High Energy Physics
18
CMS Connect
152
TG-AST150012
We request a startup allocation to support development on two related projects. The main idea is to use three dimensional simulations to constrain the histories of observed galaxies. The majority of work (1) during the initial periods of this startup will be for Graduate Student S. Alireza Mortazavi to shift an existing Condor-based pipeline at the Space Telescope Science Institute (STScI) to the Open Science Grid in order to test and plan for an ambitious expansion of his research program to constrain the dynamical histories of galaxies (Mortazavi et al. 2015). PI Snyder will also begin to develop pipelines to exploit large-scale cosmological hydrodynamical simulations (2), which predict the evolution of entire populations of galaxies in representative model universes, requiring data-intensive computing.
1. Modeling the Initial Conditions of Interacting Galaxy Pairs Using Identikit
We use the Identikit software (Barnes & Hibbard 2009, Barnes 2011; http://www.ifa.hawaii.edu/~barnes/research/identikit/ ) to model the dynamics of interacting galaxy pairs. By measuring the initial conditions of galaxy mergers, we can constrain both cosmology and galaxy astrophysics. A galactic encounter has several free parameters and it is time consuming to find the best match between model and data. However, Identikit combines multiple techniques to quickly explore parameter space to find the simulation most similar to the observed shape and constituent velocities. We have developed an automated pipeline based on the latest version of Identikit to scan parameter space and find robust matches and associated uncertainties (Mortazavi et al. 2015), implemented in an STScI-based Condor environment. We will continue to test our method against simulations of galaxy mergers to determine the systematic errors in our measurements. In addition, we will apply it to real data: We have observed a sample of ~30 interacting galaxy pairs using different telescopes. We have reached the limits of the HTCondor cluster at STScI, and therefore we seek to test the options available through XSEDE. We need around 50,000 SUs to compute matches and uncertainties of the measurements for each merging pair (observed or simulated), and so we are requesting a startup allocation of 150,000 SUs to perform tests while planning for a larger research allocation. This research will have direct applications for interpreting data from the Sloan Digital Sky Survey-IV survey "Mapping Nearby Galaxies at APO" (MaNGA).
2. Mock data applications from large hydrodynamical simulations
PI Snyder will develop methods for converting large cosmological simulations of galaxy formation (e.g., the Illustris Project www.illustris-project.org) into direct predictions for astronomical observatories. With XSEDE resources, I will seek to expand our Mock Galaxy Observatory efforts in new and ambitious directions, such as creating synthetic survey fields and advanced spectroscopic data products. For instance, we will explore the possibility of using large cosmological simulations as benchmarks for the Identikit modeling described in project 1. For testing, we are requesting 50,000 SUs on Gordon, and Data Oasis storage of 5000GB, enough to store two Illustris Simulation (or similar) outputs plus post-processed data products. In future allocation requests, we may seek to make these model archives available to the community through an XSEDE Gateway.
Gregory Snyder
Space Telescope Science Institute
Unknown
Mathematical Sciences
13
OSG-XSEDE
204
cms.org.fit
CMS Connect at Florida Institute of Technology
Marc Baarmand
Florida Institute of Technology
Physics
High Energy Physics
18
CMS Connect
59
Pheno
The goal of this project is to test and validate the Sherpa
and Blackhat software for particle physics phenomenology at the
Large Hadron Collider (LHC), and to perform studies which are directly
applicable to physics analyses in the LHC experiments ATLAS and CMS.
Sherpa is a complete Monte-Carlo event generation framework
for collider experiments. Hard scattering events are simulated
using perturbative QCD at the leading or the next-to-leading
order with the help of BlackHat. QCD Resummation is implemented
by an in-house parton shower model based on the dipole factorization
approach. Hadronization is performed in a cluster model and
a complete hadron decay simulation is included in the program.
BlackHat is a program library to compute virtual corrections
in perturbative QCD based on generalized unitarity methods.
It is used to produce particle-level cross sections for
phenomenologically relevant signal and background reactions
of high particle multiplicity at the Large Hadron Collider.
Recent progress achieved with the combination of BlackHat and
Sherpa is described at
https://twiki.grid.iu.edu/bin/view/Management/Nov2012Newsletter#Precision_Event_Simulation_for_t
Stefan Hoeche
SLAC National Accelerator Laboratory
Theory Group
High Energy Physics
30
OSG
180
NSLS2ID
Using magnetic field measurements taken in the lab of undulators and wigglers we will compute the downstream photon spectrum and distributions for many configurations of many of the NSLS2 insertion devices, including wavefront propagation and beamline simulation where needed.
Dean Andrew Hidas
Brookhaven National Laboratory
National Synchrotron Light Source II
High Energy Physics
14
OSG Connect
1292661474
FDLTCC_Wetherbee
Using Open Science Pool for 1D simulation problems
Ted Wetherbee
Fond du Lac Tribal & Community College
Mathematics
Astronomy
14
OSG Connect
535
ASU-CFD
ASU Fluid Dynamics
Bruno D. Welfert
Arizona State University
School of Mathematics and Statistical Sciences
Fluid Dynamics
14
OSG Connect
847
Caltech_Chary
Joint Survey Processing (JSP) is aimed at enabling science that requires pixel-level combination of data from the Vera C. Rubin Observatory, The Euclid Space Telescope, and the Nancy Grace Roman Space Telescope.
Ranga-Ram Chary
California Institute of Technology
IPAC
Astronomy and Astrophysics
14
OSG Connect
1732137639
MMC_Leegon
Provide services to other PIs both on campus and at other academic institutions including student training. In addition, internally we do bioinformatics research with tools such as BLAST.
Jeffrey Leegon
Meharry Medical College
Bioinformatics and Proteomics
Biological and Biomedical Sciences
14
OSG Connect
148621510
Doane_Engebretson
Parallel computing class
Alec Engebretson
Doane University
Information Science & Tech
Computer Sciences
14
OSG Connect
644
TG-CIE170019
Real-Time Optimization of High Speed Data Transfers
Engin Arslan
University of Nevada, Reno
Computer Science & Engineering
Computer and Computation Research
13
OSG-XSEDE
480
OSURHIT
Experimentally calibrated event-by-event simulations of high-energy heavy-ion collisions. Numerical implementation of optimized dissipative relativistic fluid dynamics.
Ulrich Heinz
Ohio State University
Physics Department
Nuclear Physics
14
OSG Connect
421317448
SIUE_Quinones
Research in Computer Vision, Digital Image Processing, and Multi-Agent Simulation.
Rubi Quinones
Southern Illinois University Edwardsville
Computer Science
Computer Science
2104358006
ASU_CoMSESNet
Improving the way researchers, educators and professionals develop, share, use, and re-use computational models in the social and ecological sciences
Michael Barton
Arizona State University
Center for Behavior, Institutions, and the Environment
Complex Adaptive Systems
14
OSG Connect
54
RADICAL
RADICAL: SAGA / BigJob
OSG / XSEDE interoperability and Python APIs for OSG / Condor / iRODS.
Shantenu Jha
Rutgers, The State University of New Jersey
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
291
atlas.wg.Inner-Tracking
ATLAS Connect team for Inner Tracking
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
406
selfassembly
The influence of directing agents in the self-assembly of molecular wires to produce two-dimensional electronic nanoarchitectures is studied here using a Monte Carlo approach to simulate the effect of arbitrarily locating nodal points on a surface, from which the growth of self-assembled molecular wires can be nucleated.
Eddie Tysoe
University of Wisconsin-Milwaukee
Chemistry
Chemistry
14
OSG Connect
393
TCGAPartCorr
This is a project to characterize partial correlation relationships within and between data types in the data available from The Cancer Genome Atlas (TCGA).
Chad Shaw
Baylor College of Medicine
Molecular and Human Genetics
Bioinformatics
14
OSG Connect
1109357763
PSI_Kaib
I will be using computer simulations to model the orbital evolution of comets and asteroids over the lifetime of the solar system. In addition, I will be studying the stability of the solar system and Kuiper belt as it is subjected to close flybys of other stars in the Milky Way. https://www.psi.edu/about/staffpage/nkaib
Nathan Kaib
Planetary Science Institute
Planetary Science Institute
Astronomy and Astrophysics
151711216
UWMadison_Ericksen
Molecule docking as part of drug discovery research (http://hts.wisc.edu/)
Spencer Ericksen
University of Wisconsin-Madison
Small Molecule Screening Facility
Health
1294804377
Rice_Mulligan
This project attempts to find novel geometric symmetries in the folding of polygons. It has already produced several interesting solutions, and I have now refactored it to be generalizable and linearly scalable in an HTC workflow. A small version of it serves as an example for HTC parallelization in our workshops. https://github.com/JohnMulligan/parallel_folding_example/
John Connor Mulligan
Rice University
Center for Research Computing
Mathematics and Statistics
1585206027
UTSA_Anantua
I am using Monte Carlo ray-tracing code GRMONTY to create and compare two different emission models R-Beta and Critical-Beta of M87 and Sgr A*. https://richardanantua.com/spectra/
Richard Anantua
The University of Texas at San Antonio
Department of Physics and Astronomy
Astronomy and Astrophysics
2122690389
Eureka_Danehkar
Modeling Reflection around Black Holes
Ashkbiz Danehkar
Eureka Scientific, Inc.
Eureka Scientific
Astronomy and Astrophysics
14
OSG Connect
761
UIowa_Sahin
Defects in Wide Band-gap Semiconductors for Novel Quantum Materials
Cuneyt Sahin
University of Iowa
Physics and Astronomy
Condensed Matter and Materials Physics
14
OSG Connect
576
chemml
Data-driven machine learning as surrogates for quantum chemical methods. Data from the project will be made open to improve existing quantum ML methods as well as next generation atomistic force fields.
Geoffrey Hutchison
University of Pittsburgh
Chemistry
Chemistry
14
OSG Connect
547
TG-MCB170126
Demographic analysis using ARGweaver
Melissa Hubisz
Cornell University
Biological Statistics and Computational Biology
Genetics and Nucleic Acids
13
OSG-XSEDE
605
LSUHSC_CanavierLab
Nonlinear dynamics of single neurons and networks
Carmen Canavier
Louisiana State University Health Sciences Center
Cell Biology and Anatomy
Neuroscience
14
OSG Connect
1236668135
Training-ACE-NIAID
Group for ACE training (through NIAID/NIH)
Mariam Quiñones
NIAID/NIH
Bioinformatics and Computational Biosciences Branch (BCBB)
Training
14
OSG Connect
184
TextLab
Data analytics on available text with python programs
James Evans
University of Chicago
Computation Institute
Multi-Science Community
14
OSG Connect
279
atlas.org.uta
ATLAS Connect team for University of Texas - Arlington
Robert William Gardner Jr
University of Texas at Arlington
Physics
High Energy Physics
16
ATLAS Connect
129
SWC-OSG-UC14
Software Carpentry/OSG Workshop at University of Chicago. Date Dec 15-17 2014.
Robert William Gardner Jr
University of Chicago
Computation Institute
Computer and Information Science and Engineering
14
OSG Connect
677
COVID19_RepertoireTCell
Predicting Long-Term T Cell Responses to SARS-CoV-2 via Molecular Modeling and Machine Learning https://covid19-hpc-consortium.org/projects/5ebf07523e6ec40081202fac
The dynamics of COVID-19 infection remain poorly understood, and it is unknown whether patients acquire prolonged immunity to the virus following initial infection. Most current vaccine efforts mainly promote B cell production of neutralizing antibodies. While often critical for virus neutralization and disease control, research from the 2002-2003 SARS-CoV epidemic suggests that B cells and serum antibodies involved in the initial immune response are likely to be short-lived. However, many patients with undetectable antibody levels retained immune protection by virtue of long-lived T cells, and correlation of T cell recovery with convalescence in COVID-19 strongly suggests that T cells are critical for virus control. By computationally simulating hundreds of thousands of interactions between T cells and COVID-19-infected cells, we aim to characterize the biochemical features of T cells responsible for long-term COVID-19 immunity and identify a small number of viral molecules that have the highest likelihood of inducing long-term immunity when delivered through vaccines.
Michael Noble
Repertoire Immune Medicines
Computational Sciences
Biological and Biomedical Sciences
14
OSG Connect
112
CentaurSim
Centaurs are icy objects in the outer solar system whose orbits cross those of the giant planets. It is thought that most Centaurs originate from the solar system's Kuiper Belt, a reservoir of icy bodies orbiting just beyond Neptune. However, a few Centaurs with very large orbital inclinations and/or mean orbital distances cannot be well-explained with a Kuiper Belt origin. Alternatively, it has been proposed that these outlier Cenaturs may come from the Oort Cloud, a spherical halo of icy objects that extends over halfway to the nearest star. In this project we will simulate the production of Centaurs from the Oort Cloud using numerical orbital integrations. Following this, we will run our simulated orbits/objects through a sky survey simulator to compare our simulated "detections" with the real sample of known objects. Thus, we will be able to evaluate whether the Oort Cloud is a potential source of Centaurs with extreme orbits.
Nathan Kaib
Northwestern University
Physics and Astronomy
Astrophysics
14
OSG Connect
529
UCF_IT
Project for UCF IT staff for exploring and using OSG Connect
Tim Larson
University of Central Florida
Information Technolgoy
Technology
14
OSG Connect
662
UChicago_Barton
Exploring Data Caching and Federation on the OSG
Thomas Barton
The University of Chicago
Information Technology Services
Infrastructure Development
14
OSG Connect
323
Lg-Attenuation
Determine the attenuation of the regional shear wave Lg for NE China and the contiguous United States using broadband seismograms.
Andrea C Gallegos
New Mexico State University
Earth Sciences
Earth Sciences
14
OSG Connect
468
lychrelsearch
This project will search for and perform limited verification of potential Lychrel numbers. A Lychrel number is a natural number that through reversing its digits and adding them together, repeatedly, does not form a palindrome.
James P. Howard, II
Johns Hopkins University
Mathematics
Mathematical Sciences
14
OSG Connect
538
VolcanoTomography
Volcano Tomography Using Cosmic Ray Muons
David Martinez Caicedo
South Dakota School of Mines and Technology
Physics
Physics
14
OSG Connect
22
KnowledgeSys
In educational assessment, several questions must be answered when constructing a test, such as “How many items are necessary for adequate knowledge measurement precision?”, “How many field-test students are needed to adequately calibrate model parameters?”, or “Which computerized adaptive testing (CAT) algorithm performs best?” For complex non-linear models, these questions are typically approached by simulation: Model parameters are calibrated (as if unknown) from simulated student item responses, or the emergent properties of particular CAT algorithms are investigated with a large number of simulated test takers. Since the design space grows quickly, many simulations are necessary to understand general trends.
Match-for-OSG:
Simulations throughout the test design space can be run independently, requiring little coordination between cores. Computations generally do not have high memory requirements or unusual library/code dependencies, and computations can be recovered from checkpoints easily. The large number of simulations suggests parallel computing, but the independence allows an asynchronous, distributed environment, such as OSG.
Michael J. Culbertson
University of Illinois Urbana-Champaign
Psychology
Educational Psychology
14
OSG Connect
341
GeoTunnel
Analyzing muon data to obtain information about the objects they traversed.
Elena Guardincerri
Los Alamos National Lab
Physics
Nuclear Physics
14
OSG Connect
11780412
HCC_staff
Cyberinfrastructure Research
Adam Caprez
University of Nebraska-Lincoln
Holland Computing Center
Computer Science
42915845
Washington_Savage
Quantum simulations of many-body systems for nuclear and high-energy physics (https://iqus.uw.edu).
Martin J. Savage
University of Washington
IQuS, Department of Physics
Physics
14
OSG Connect
255
atlas.org.iastate
ATLAS Connect team for Iowa State University
Robert William Gardner Jr
Iowa State University
Physics
High Energy Physics
16
ATLAS Connect
278
atlas.org.upenn
ATLAS Connect team for University of Pennsylvania
Robert William Gardner Jr
University of Pennsylvania
Physics
High Energy Physics
16
ATLAS Connect
277
atlas.org.uoregon
ATLAS Connect team for University of Oregon
Robert William Gardner Jr
University of Oregon
Physics
High Energy Physics
16
ATLAS Connect
500
mars
Dummy project corresponding to the mars VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
556
TG-DBS170012
Europa Lander Orbital Tours
James Howard
Johns Hopkins University Applied Physics Lab
Advanced Scientific Computing
13
OSG-XSEDE
2002238008
IU-PTI_Airavata
Project for Airavata gateway deployments
Rob Quick
Indiana University
Pervasive Technology Institute
Computer and Information Sciences
14
OSG Connect
859221248
TG-CHM210003
This will allow for the determination of relative solubility of polymeric materials in alcohol solvents, similar to the shampoo and shaving cream materials. An understanding of the free energy of solvation and surface activity of polyethers and polysilicones will allow for the optimization of alcohol content in such mixtures to get the best bang for the buck in solubilizing and surface tension optimized alcohol-water mixtures with these polymers present.
Guy Mongelli
University of Rochester
Chemical Engineering
Chemical Engineering
14
OSG Connect
343784385
SBU_Jia
https://www.stonybrook.edu/commcms/chemistry/faculty/_faculty-profiles/jia-jiangyong Simulation of relativistic heavy ion collisions of atomic nuclei, such as Gold, Lead, Xeon, Oxygen, proton etc using relativistic hydrodynamic code and transport simulation codes.
Jiangyong Jia
State University of New York at Stony Brook
Physics
Physics
902788060
FIU_Guo
My research in experimental nuclear physics requires large amounts of simulations. These simulations are independent of one another and the OSPool is very well suited for these tasks. Access to the OSG computing resources would be a useful asset for my research.
Lei Guo
Florida International University
College of Arts and Science
Physics
286
atlas.wg.combined-muon
ATLAS Connect team for Combined Muon
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
146
TG-SES090019
Geographic Information Science (GIScience), crosscutting many fields (e.g., geography, social sciences, computer science, geodesy, and information sciences), plays essential roles for transforming geographic data into geospatial information and knowledge, breaking through scientific problems, and improving decision-making practices of broad and significant societal impact. However, fulfilling such roles is increasingly dependent on the ability to handle very large spatial datasets and complex analysis and modeling methods based on synthesizing computational and spatial thinking enabled by cyberinfrastructure (CI), which conventional GIS software approaches do not provide. CI-based integration of geographic information systems (GIS) and spatial analysis and modeling, as a holistic solution, is leading to unprecedented capabilities for transforming geospatial sciences.The purpose of this project is to extend and sustain GISolve, a TeraGrid Science Gateway toolkit for GIScience, for establishing a high performance, distributed, and collaborative CyberGIS framework that couples CI, GIS, and geospatial analysis and modeling capabilities. Through the continuous TeraGrid resource allocation support from previous three years, a set of spatial middleware components has been built into the GISolve Toolkit to glue generic cyberinfrastructure capabilities and geospatial analysis methods. This toolkit has been used to build the TeraGrid GIScience Gateway as a collaborative geospatial problem-solving environment for multi-disciplinary researchers to perform large-scale geospatial analysis and modeling, and help non-technical users directly benefit from accessing TeraGrid capabilities. With the support of TeraGrid high-end computing resources, we have developed a set of high-performance parallel and distributed geospatial computational methods for our research projects. Scalability and efficient use of high-end computing resources are the foci in developing these methods. For example, the parallel agent-based modeling and parallel land use optimization code are scalable to thousands of processors on Abe and Ranger with impressive computational performance. The methods so developed have been applied in solving large- and multi-scale geospatial science problems that could not be solved before, such as the study of geospatial pattern of the impact of global climate change on crop yields. With GISolve being widely used in the GIScience community, new methods continue to be identified, proposed, and integrated in the GISolve Toolkit. To support community-contributed applications, we have developed a streamlined application integration process to facilitate cyberinfrastructure-enabled computation and efficient integration into the science gateway for sharing. This project has been growing dramatically with consistent and extended research collaboration and education efforts such as the collaboration with the U.S. Geological Survey (USGS) in the National Map project and outreach activities with the University Consortium for Geographic Information Science (UCGIS).
Shaowen Wang
University of Illinois Urbana-Champaign
Geography and Geographic Information Science
Geographic Information Science
13
OSG-XSEDE
548
TG-MCB190026
Global and Local Matching of Electron Microscopy Density Maps
Daisuke Kihara
Purdue University
Biological Sciences/Computer Science
Biophysics
13
OSG-XSEDE
573
TG-AST190031
The Resonance Hopping Effect in the Neptune-Planet Nine System
Tali Khain
University of Chicago
Physics
Planetary Astronomy
13
OSG-XSEDE
660
COVID19_Stanford_Das
RNA tertiary structure of COVID-19 UTRs as therapeutic and vaccine targets: https://daslab.stanford.edu/news
Rhiju Das
Stanford University
Biochemistry
Biological and Biomedical Sciences
14
OSG Connect
329
Clemson
HTC training for the computational scientist at Clemson University.
Marcin Ziolkowski
Clemson University
Computational Science
Multi-Science Community
14
OSG Connect
1963393930
UC-Staff
UC staff - testing and monitoring
Robert William Gardner Jr
University of Chicago
Physics
Computer Science
30
OSG
122
psims
A framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and
converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS
accelerates computational research, encourages model intercomparison, and enhances reproducibility of
simulation results.
Joshua Elliott
University of Chicago
Computation Institute
Earth Sciences
14
OSG Connect
317
seq2fun
We combine innovative high-throughput experiments with data mining approaches to identify functional regulatory elements in biological sequence, building the foundation for further experiments to map complete regulatory networks.
Peter Freddolino
University of Michigan
Biological Chemistry
Bioinformatics
14
OSG Connect
192
TechEX15
Internet2 -TechEX15 Workshop on High Throughput Computing October 8th 2015
Robert William Gardner Jr
University of Chicago
Computation Institute
Multi-Science Community
14
OSG Connect
689540769
UWMadison_Chen
Quantifing future forest productivity change and its impact on global land use and land cover change under global climate change.
Min Chen
University of Wisconsin-Madison
Department of Forest and Wildlife Ecology
Agricultural Sciences
14
OSG Connect
271007651
Hawaii_Dodds
We experimentally develop efficient means of distribution to federated national cyberinfrastructure (CI) platforms of Hawaii astronomy big data sets. We will demonstrate use of these data sets with OSG and other CI platforms using SOTA AI/ML research methods applied to astronomy and astrophysics research questions. We hope to publish a collection of canonical ML models that work efficiently with these astronomy big data sets utilizing national, regional and campus CI resources.
Stanley Dodds
University of Hawaii at Manoa
Institute for Astronomy
Computer and Information Sciences
14
OSG Connect
413
DeepMail
To develop a contextual search technique on a given text corpus. The idea is to develop a search model using Deep Learning techniques and Natural Language Processing. More specifically, we are currently exploring Word Embedding techniques in NLP and Neural Network models like Word2Vec. The model would first train itself on the existing email corpus of a given user and then be able to provide search results based on contextual queries.
Micheal Marasco
Northwestern University
Farley Center for Entrepreneurship and Innovation
Computer and Information Science and Engineering
14
OSG Connect
292
atlas.org.Jet-EtMiss
ATLAS Connect team for Jet EtMiss
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
611
FF15IPQEXT
Parameterizing force fields for artificial amino acids through molecular dynamic simulations
Lillian Chong
University of Pittsburgh
Chemistry
Chemistry
14
OSG Connect
1722643692
MontgomeryCollege_Dillman
workforce training, 2-5 day workshops every couple of months to get bench biologists comfortable with various bioinformatics pipelines on the command line.
Allissa Dillman
Montgomery College
Workforce Development & Continuing Education
Biological and Biomedical Sciences
14
OSG Connect
750
Cornell_Gage
Genomic basis of maize protein abundance dysregulation
Joseph Gage
Cornell University
Institute for Genomic Diversity
Agricultural Sciences
14
OSG Connect
1771702212
SDState_RCi
This project will be used to train RCi staff in delivering OSG to researcher at SDSU.
Chad Julius
South Dakota State University
Research Cyberinfrastructure
Computer Science
14
OSG Connect
104
unlcpass
The Comparison of Protein Active Site Structures (CPASS) database and software is used as part of our FAST-NMR assay to assign the function of a hypothetical protein or a protein of unknown function. The CPASS database and software enable the comparison of experimentally identified ligand binding sites to infer biological function and aid in drug discovery. The CPASS database is comprised of unique ligand-defined active sites identified in the Protein Data Bank, and the CPASS program compares these ligand-defined active sites to determine sequence and structural similarity without maintaining sequence connectivity, along with ligand similarity, if desired. CPASS will compare any set of ligand-defined protein active sites irrespective of the identity of the bound ligand.
Adam Caprez
University of Nebraska-Lincoln
Bioinformatics
Bioinformatics
67
HCC
75
StanfordRCC
This project is for simulation work in the Stanford research community.
Ruth Marinshaw
Stanford University
RCC
Community Grid
14
OSG Connect
17
AtlasConnect
To support ATLAS Tier 3 flocking into Tier 1 and Tier 2 centers and to support an OSG Connect-like service dedicated to the US ATLAS Collaboration.
The ATLAS detector studies physics at the energy frontier at the Large Hadron Collider in Geneva, Switzerland.
Robert William Gardner Jr
University of Chicago
Computation and Enrico Fermi Institutes
High Energy Physics
14
OSG Connect
622882552
SDSC-Staff
San Diego Supercomputing Center staff, for system exploration and integration
Frank Wuerthwein
University of California, San Diego
San Diego Supercomputing Center
Computer Sciences
14
OSG Connect
397
SOL
The goal of this project is to implement Sol (a set of programs to compute solar insolation on complex landscapes and the energy available to drive weathering).
Tyson Swetnam
University of Arizona
Geosciences
Geographic Information Science
30
OSG
182
ncidft
Project Description: Density-Functional Theory (DFT) is the most successful method for the computation of quantum mechanical properties in molecules and solids. The aim of our project is to advance the DFT field by extending and improving the existing methods for modeling non-covalent interactions. Computational tasks for this project include DFT calculations on small molecules as well as periodic solids, and the use of home-made programs that implement our methodologies.
Alberto Otero de la Roza
National Research Council of Canada
National Institute for Nanotechnology
Chemistry
14
OSG Connect
441
extinction
Population dynamics simulations in R and Python will be used to understand how increasing environmental variability due to climate change and habitat degradation interact and affect a species' time to extinction.
Shripad Tuljapurkar
Stanford University
Biology
Ecological and Environmental Sciences
14
OSG Connect
604
RPI_Brown
Event reconstruction in nanoscale layers for detection of neutrino decay
Ethan Brown
Rensselaer Polytechnic Institute
Physics
Elementary Particle Physics
14
OSG Connect
836
TexasTech_Corsi
Detection of gravitational waves from transient signals using LIGO data.
Alessandra Corsi
Texas Tech University
Physics and Astronomy
Physics
14
OSG Connect
52
NWChem
The goal of this work is to provide a federated heterogeneous infrastructure that can be federated on demand for scientists and scientific applications. The goal of this work is to integrate OSG as a part of the federated infrastructure cloud. The federation leverages the CometCloud software, currently being developed at Rutgers University. NWChem is the initial application to be used on OSG resources. A parallel in time algorithm will run multiple NWChem instances on the OSG resources, where each instance has different input parameters. The collective output of all instances is then gathered and analyzed.
Manish Parashar
Rutgers, The State University of New Jersey
Electrical & Computer Engineering
Computer and Information Science and Engineering
30
OSG
886033397
UCDenver_Gaffney
Musculoskeletal Biomechanics of Amputees
Brecca Gaffney
University of Colorado Denver
CEDC-Mechanical Engineering
Engineering
14
OSG Connect
95
ProtFolding
Study statistical machine learning and optimization algorithms for data-driven protein structure prediction, by learning sequence-structure relationship from existing protein sequence and structure data.
Jinbo Xu
Toyota Technological Institute at Chicago
Computer Science
Bioinformatics
14
OSG Connect
568
LancasterPPS
Lancaster Muon g-2 Experiment Beam Dynamics
Ian Bailey
Lancaster University
Physics
Physics
14
OSG Connect
244568524
JHU_Zhang
Condensed matter theory with a focus on strongly correlated physics.
Yahui Zhang
Johns Hopkins University
Department of Physics
Physics
330
TG-CHE150012
The overarching goal of the research to be performed using XSEDE resources is to characterize the thermodyanmic and dynamic driving forces for the behavior and properties of systems at the molecular level. This work will involve calculation of molecular free energies of transfer between different systems, molecular flow in nanoporous materials, determination and refinement of molecular interactions in different environments, and simulations of biomolecular systems. One key focus of this work will by on optimizing our use of co-processor hardware, the Intel Xeon Phi cards in particular, to facilitate our brand of scientific discovery.
Christopher Fennell
Oklahoma State University
Chemistry
Chemistry
13
OSG-XSEDE
687
COVID19_Harvard_Bitran
Designing Inhibitors of SARS-CoV 2 Spike Protein Folding
The receptor binding domain (RBD) of the SARS-CoV 2 Spike (S) protein plays a crucial role in enabling the virus to enter host cells, and represents a promising target for antiviral drugs. A common therapeutic strategy involves deploying small molecules to inhibit the protein-protein interaction (PPI) between the RBD and the human angiotensin-converting enzyme 2 (ACE2) to which it binds. But unfortunately, it is difficult to inhibit such PPIs using small molecules due to the large interaction surface area involved. To overcome this difficulty, we propose to develop a novel antiviral strategy whereby small molecules will be used to specifically bind and stabilize intermediates in the RBD folding pathway, thus inhibiting the domain’s folding and promoting the S protein’s degradation. Using folding simulations, we plan to map the RBD’s folding pathway in atomistic detail and identify long-lived intermediates with well-defined binding pockets. We will then identify existing, as well as newly-designed small molecules that bind these cavities with high affinity, but do not bind the native state. The resulting hits will then be experimentally screened for their ability to inhibit RBD folding and their antiviral activity. If successful, this approach will yield a novel therapeutic strategy against SARS-CoV 2 that overcomes difficulties associated with most RBD inhibitors. Furthermore, we expect it will be difficult for SARS-CoV 2 to acquire resistance to these folding inhibitors, owing to severe fitness costs associated with mutating residues that are surface-exposed in folding intermediates.
Amir Bitran
Harvard University
Chemistry and Chemical Biology
Chemistry
14
OSG Connect
186
QEvolBiol
Quantitative approaches to evolutionary biology including numerical analysis of mathematical models of evolutionary change and individually-based simulations of population dynamics, mutation, natural selection, and other evolutionary forces.
Jeremy Van Cleve
University of Kentucky
Biology
Biological and Critical Systems
14
OSG Connect
2051187213
UCI_Sheng
Research on the US housing market and transactions with the aim of comprehending how housing prices move and are correlated with each other.
Jinfei Sheng
University of California, Irvine
Paul Merage School of Business
Economics
303
TG-TRA150018
A request for initial campus champion resources for Oregon State University researchers.
Stephen Wolbers
Oregon State University
Information Services
Other
13
OSG-XSEDE
700
UCSD_Kandes
Brute-Force Search for Nonlinear Enhancements to the Sagnac Effect in Matter Waves
Martin Charles Kandes
University of California, San Diego
San Diego Supercomputing Center
Physics
14
OSG Connect
288
atlas.wg.Flavour-Tagging
ATLAS Connect team for Flavour Tagging
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
316
polyHERV
Fine-mapping of human endogenous retrovirus polymorphisms
Gkikas Magiorkinis
University of Oxford
Zoology
Bioinformatics
14
OSG Connect
195
TG-AST150044
We are requesting 1,700,000 SUs on Open Science Grid to model the initial conditions of a sample of 15 major galaxy mergers in the local universe. These measurements will place unique constraints on the role of galaxy mergers in shaping galaxy evolution, and on cosmological assembly. Our sample consists of 15 interacting galaxy pairs with Hα kinematic maps, 2 of which have both Hα and HI 2D kinematic maps and 3 of which are drawn from the SDSSIV MaNGA survey. We will use the Identikit software package (Barnes & Hibbard 2009; Barnes 2011) and our automated pipeline to model the dynamics of interacting galaxy pairs and constrain their initial orbital parameters and merger stage.
Jennifer Lotz
Space Telescope Science Institute
Astronomical Sciences
Astrophysics
13
OSG-XSEDE
609
BCH_Holt
Molecular Evolution and Phylogenetics
Jeffrey Holt
Boston Children's Hospital
Biological and Biomedical Sciences
14
OSG Connect
292073190
NOAA_Bell
Water column sonar data, the acoustic back-scatter from the near surface to the seafloor, are used to assess physical and biological characteristics of the ocean including the spatial distribution of plankton, fish, methane seeps, and underwater oil plumes. Currently our catalog includes 270 TB of data that we are working to convert from a proprietary industry format into a cloud native Zarr format. Further documentation: <https://cires.gitbook.io/ncei-wcsd-archive/>
Carrie Bell
National Oceanic and Atmospheric Administration
Cooperative Institute for Research in Environmental Sciences
Ocean Sciences
49
TG-ASC130043
The proposed project aims to decrease the management overhead and code complexity of trajectory analysis from particle simulation data. Particle simulations produce trajectories, which are encoded by a stream of high-dimensional vectors (frames). Analysis on this data usually takes a map-reduce form consisting of mapping each frame to successively smaller vectors of descriptors.From this starting point, two typical data analysis cases will be considered. The first is statistical, through construction of order statistics, histograms, cumulants, or weighted averages. We will develop code generation methods to handle general nonlinear analysis functions. The second analysis goes one step further by fitting the analyzed data to an assumed functional form using Bayesian inference.Due to the map-reduce structure of these computations, these analysis methods can be parallelized while retaining a high-level programming model. This task requires automated consideration of data movement and task separation to match available computational resources. The result will be published under an open source license, and be immediately useful to computational chemistry and biology applications analyzing large molecular dynamics simulations.This work will make use of the open science grid and Pegasus software as well as the TACC Longhorn data analysis cluster for systems and application comparison. Project code storage on XWFS and scratch access on TACC will also be needed. FutureGrid may be explored for compatibility with the Unicore workflow specification and Pegasus if its production status is extended past September.
David Rogers
University of South Florida
Chemistry
Computer and Information Science and Engineering
13
OSG-XSEDE
757
CUBoulder_Aydin
Protein design algorithms
Halil Aydin
University of Colorado Boulder
Biochemistry
Biological Sciences
14
OSG Connect
471
panorama
Performance Data Capture and Analysis for End-to-end Scientific Workflows
Georgios Papadimitriou
University of Southern California
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
714
clas12MC
Jefferson Laboratory Hall-B CLAS12 project
Maurizio Ungaro
Jefferson Lab
Physics
Nuclear Physics
14
OSG Connect
751
Utah_Chipman
Designing Adaptive Clinical Trials
Jonathan Chipman
University of Utah
Population Health Sciences
Biostatistics
14
OSG Connect
717004860
MSState_2024_Chen
This project is dedicated to creating a comprehensive multimodal platform, specifically designed to enhance graph dynamics analytics in professional settings.Our goal is to encompass the complete life cycle of graph dynamics with particular emphasis on spatial trajectory mining, including location prediction, optimal routing inference, and identity recognition. Central to this initiative is utilization the capabilities of large transformer models (e.g., Large Language Models, Vision Transformers, or Graph Transformers). These will be tailored to effectively capture the complexities inherent in trajectory over spatial graphs. By leveraging natural language, we can unlock the potential of advanced graph analytics to those without programming expertise, and enable seamless collaboration between experts across domains by speaking the universal language.
Zhiqian Chen
Mississippi State University
Computer Science and Engineering
Computer and Information Services
334465912
IIT_Zhong
We conduct research on scientific machine learning, especially related to how machine learning can be used to learn and understand dynamical systems from observation data. Right now, we are developing models to understand synchronization, i.e. how oscillators can be put in sync with spatial patterns.
Ming Zhong
Illinois Institute of Technology
Appleid Mathematics
Appleid Mathematics
14
OSG Connect
568705068
UCSD_Shah
The Shah lab develops biomaterials to direct immune activity and function.
Nisarg Shah
University of California, San Diego
Nanoengineering Department
Engineering
14
OSG Connect
1942328054
IceCube_2022_Halzen
IceCube is the world's largest neutrino detector. It is located at the South Pole and includes a cubic kilometer of instrumented ice. IceCube searches for neutrinos from the most violent astrophysical sources: events like exploding stars, gamma ray bursts, and cataclysmic phenomena involving black holes and neutron stars. The IceCube telescope is a powerful tool to search for dark matter, and could reveal the new physical processes associated with the enigmatic origin of the highest energy particles in nature. In addition, exploring the background of neutrinos produced in the atmosphere, IceCube studies the neutrinos themselves; their energies far exceed those produced by accelerator beams.
Francis Halzen
University of Wisconsin-Madison
Physics
Astrophysics
21
PATh Facility
455
Diffusion-predictor
Diffusion predictor from IU Brain Science
Soichi Hayashi
Indiana University
Brain Science
Neuroscience
30
OSG
237
cms.org.rochester
CMS Connect at University of Rochester
Regina Demina
University of Rochester
Physics
High Energy Physics
18
CMS Connect
1006663596
TG-TRA220017
Campus Champions Request for the University of South Dakota
Bill Conn
University of South Dakota
ITS
Training
14
OSG Connect
433
NGNDA
The goal of this project is to develop and deploy a novel computational platform for massive parallel analysis
of high-dimensional brain networks.
Caterina Stamoulis
Harvard Medical School
Medicine
Medical Sciences
14
OSG Connect
180924149
UNI_Staff
Will be using OSPool to evaluate and develop training for UNI users.
Wesley Jones
University of Northern Iowa
Information Technology, Network & Infrastructure Services
Training
138
SWC-OSG-IU15
Joint Software Carpentry/OSG Workshop at IUPUI, March 3rd-6th 2015.
Robert William Gardner Jr
IUPUI
OSG
Community Grid
14
OSG Connect
804
MIT_Chakraborty
Using computational methods to study the adaptive immune system; simulating the processes of affinity maturation in order to improve vaccine design.
Arup Chakraborty
Massachusetts Institute of Technology
Chemical Engineering
Biological and Biomedical Sciences
14
OSG Connect
10
RIT
Ramsey theory studies the properties that combinatorial structures need in order to guarantee that desired substructures are contained within them. It is often seen as the study of the order that comes from randomness, and has applications in mathematics, computer science, finance, economics, and other areas. Our research involves a computational approach to establishing the values of various Ramsey numbers, whose role is to quantify the general existential theorems in Ramsey theory.
Stanisław P. Radziszowski
Rochester Institute of Technology
Computer Science
Computer and Information Science and Engineering
30
OSG
497
networkdist
Measuring driving and walking times for very large matrices of points.
James Saxon
University of Chicago
Harris School of Public Policy
Earth Sciences
14
OSG Connect
269
atlas.org.smu
ATLAS Connect team for Southern Methodist University
Robert William Gardner Jr
Southern Methodist University
Physics
High Energy Physics
16
ATLAS Connect
622
UCF_GRIT
UCF's Graduate and Research Information Technology (GRIT) provides innovative and effective digital services that are strategically aligned to the goals of research and graduate programs.
Ozlem Garibay
University of Central Florida
Office of Research and Graduate Studies
Research Computing
14
OSG Connect
353
TG-AST160036
Starspots are dark regions on a star's surface that trace areas of strong magnetic fields. On the Sun, spots are typically small and occur in bands near the stellar equator. Sunspot occurrence frequency also peaks every 11 years due to the "solar cycle". For younger stars there are indications that spots are larger, and can form near the stellar poles, while evidence for spot activity cycles on other stars is sparse. These differences indicate that the shape and strength of the internal magnetic dynamo evolves throughout a stars life. However, because of their great distance we cannot directly observe the surface of other stars to map the locations and sizes of spots. We have developed new software to model the signature of starspots in Kepler data from transiting exoplanet systems. These star-planet systems are unique in having an orbiting planet that passes directly in front of its parent star. When the planet transits the star, it will briefly pass over spots on the star's surface, giving a very small change in the apparent brightness of the system. To trace the evolution of spot size and location with stellar age we must extend our analysis to many star systems with different transiting planet orientations. A startup allocation from XSEDE will allow us to test our software's ability to map spots from different system orientations, and using many years worth of Kepler data.
James Davenport
Western Washington University
Physics
Astrophysics
13
OSG-XSEDE
270
atlas.org.stonybrook
ATLAS Connect team for State University of New York — Stony Brook
Robert William Gardner Jr
State University of New York at Stony Brook
Physics
High Energy Physics
16
ATLAS Connect
652
MCBI
processing images with Freesurfer
Davide Momi
Harvard University
Martinos Center for Biomedial Imaging
Medical Imaging
14
OSG Connect
58267066
Emory_Boettcher
Finite-size corrections in spin glasses and combinatorial optimization
Stefan Boettcher
Emory University
Department of Physics
Condensed Matter Physics
14
OSG Connect
825
BU_Mu2e
Mu2e is a muon-to-electron-conversion particle physics experiment at Fermilab
Jim Miller
Boston University
Physics
Physics
14
OSG Connect
816055629
TG-CIE170004
This allocation enables Globus help desk and tech support personnel to troubleshoot issues and provide technical support for the Globus endpoints operated by ACCESS resource providers.
Lee Liming
University of Chicago
Globus Staff
Applied Computer Science
14
OSG Connect
1116387884
UNL_Weitzel
Cyberinfrastructure Research
Derek Weitzel
University of Nebraska-Lincoln
Computer Science and Engineering
Computer Science
14
OSG Connect
72
TG-TRA120014
This is the allocation for my Montana State University Campus Champion account.
Pol Llovet
Montana State University
Research Computing Group
Evolutionary Sciences
13
OSG-XSEDE
248
atlas.org.arizona
ATLAS Connect team for University of Arizona
Robert William Gardner Jr
University of Arizona
Physics
High Energy Physics
16
ATLAS Connect
582
CLAS12
Jefferson Laboratory Hall-B CLAS12 project
Maurizio Ungaro
Jefferson Lab
Physics
Nuclear Physics
99
JLab
26
Swift
Software development and systems testing for the parallel scripting language.
Kyle Chard
University of Chicago
Computation Institute
Computer Sciences
14
OSG Connect
423
DTWclassifier
Pattern classifier of neuronal responses with dynamic time warping as a distance measure.
Luke Remage-Healey
University of Massachusetts Amherst
Psychological and Brain Sciences
Neuroscience
14
OSG Connect
207
cms.org.ufl
CMS Connect at University of Florida
Gena Mitselmakher
University of Florida
Physics
High Energy Physics
18
CMS Connect
722
WayneStateU_Pique-Regi
Cracking the gene regulatory grammar
Roger Pique-Regi
Wayne State University
Center for Molecular Medicine and Genetics
Biological Sciences
14
OSG Connect
250
atlas.org.brandeis
ATLAS Connect team for Brandeis University
Robert William Gardner Jr
Brandeis University
Physics
High Energy Physics
16
ATLAS Connect
597
UCMerced_Han
Water Research in University of California Merced
Liang Shi
University of California, Merced
Chemistry and Chemical Biology
Chemistry
14
OSG Connect
19
CompNeuro
To give you a brief idea, I am trying to identify the information flow
among several brain regions in rats in the neuronal level. The rats
were actively doing a aperture discrimination task (whether a gate
opened wide or narrow). I wish to find not only the static neuronal
circuitry of the sensory input, but also the dynamics of the flow
across time.
Po-He Tseng
Duke University
Neurobiology
Neuroscience
14
OSG Connect
753
MTU_Zhang
Statistical genetics
Kui Zhang
Michigan Technological University
Mathematical Sciences
Mathematics
14
OSG Connect
595
GATech_Randall
Self Organizing Particle Systems
Dana Randall
Georgia Institute of Technology
Computer Science
Computer Science
14
OSG Connect
76
AlGDock
Binding Potential of Mean Force Calculations with Alchemical Interaction Grids
Standard binding free energies are frequently sought in drug design. According to implicit ligand theory, standard binding free energies can be determined from binding potential of mean force (PMF) calculations from different receptor structures. Binding PMFs are a special type of binding free energy in which the receptor is rigid. The purpose of this project is to develop methods for estimating binding PMFs.
David Minh
Illinois Institute of Technology
Chemistry
Chemistry
14
OSG Connect
602
TexasAM_Alsmadi
Analysis of Twitter posts to determine defining characteristics of bots for identification.
Izzat Alsmadi
Texas A&M University
Computer and Information Services
Computer and Information Services
14
OSG Connect
211
cms.org.uiowa
CMS Connect at University of Iowa
Yasar Onel
University of Iowa
Physics
High Energy Physics
18
CMS Connect
725
UNOmaha_Chase
Training neural networks to track animal movement
Bruce Chase
University of Nebraska Omaha
Psychology
Biological Sciences
14
OSG Connect
94
dVdT
The main goal of the project is to design a computational framework that enables computational experimentation at scale while supporting the model of “submit locally, compute globally”. The project focuses on estimating application resource needs, finding the appropriate computing resources, acquiring those resources, deploying the applications and data on the resources, managing applications and resources during run. The project also aims to advance the understanding of resource management within a collaboration in the areas of: trust, planning for resource provisioning, and workload, computer, data, and network resource management.
Ewa Deelman
University of Southern California
Information Sciences Institute
Computer and Information Science and Engineering
30
OSG
660
COVID19_WeNMR
COVID-19 research through the WeNMR portal, HADDOCK (https://www.eosc-hub.eu/news/haddock-support-covid-19-research)
WeNMR is a Virtual Research Community supported by EGI. WeNMR aims at bringing together complementary research teams in the structural biology and life science area into a virtual research community at a worldwide level and provide them with a platform integrating and streamlining the computational approaches necessary for data analysis and modelling.
Alexandre Bonvin
Utrecht University
N/A
Biological Sciences
73
ENMR
380
duke-bgswgs
To study the genomic and genetic aspects of brainstem gliomas
Hai Yan
Duke University
Pathology
Bioinformatics
15
Duke
2061809859
MSU_ICERStaff
Group for ICER (Institute for Cyber Enabled Research) staff at Michigan State
Dirk Colbry
Michigan State University
Institute for Cyber Enabled Research
Research Computing
14
OSG Connect
352
duke-CMT
We are condensed-matter theorists at Duke. We study the onset of strong correlation in various setups, such as qubits coupled to a 1D waveguide and impurities immersed in an electromagnetic environment. With the aid of the OSG distributive environment, we are able to solve problems using a variety of numerical approaches, including but not limited to quantum Monte Carlo, quantum jumps, etc.
Harold U. Baranger
Duke University
Physics
Computational Condensed Matter Physics
15
Duke
750
TG-PHY140048
Campus Champion Allocation -- APSU
Justin Oelgoetz
Austin Peay State University
Physics, Engineering & Astronomy
Science and Engineering Education
13
OSG-XSEDE
598100763
Caltech_Morrell
Access to OSDF data resources
Tom Morrell
California Institute of Technology
Library
Computer and Information Sciences
14
OSG Connect
141
cms.org.ucsd
CMS Connect group for UCSD
Frank Wuerthwein
University of California, San Diego
Physics
High Energy Physics
18
CMS Connect
276
atlas.org.unm
ATLAS Connect team for University of New Mexico
Robert William Gardner Jr
University of New Mexico
Physics
High Energy Physics
16
ATLAS Connect
698
UWMadison_Wright
Project for Daniel Wright's research group at UW-Madison
Daniel Wright
University of Wisconsin-Madison
Civil and Environmental Engineering
Civil Engineering
14
OSG Connect
429
colorcat
Different languages divide the visible light spectrum into words (e.g. "red," "green," "blue" ... in English) in different ways. However, despite the apparent freedom in assigning colors to different categories, there are clear universal patterns across languages in how they divide color space according to the number of color terms in the language. This pattern has now been empirically well established, however there remains a confusion of theories for why this pattern should exist at all. In fact, a simple, evolutionary model in tandem with a model of perceptual color space and color saliency, completely accounts for the observed universal patterns. We will use the open science grid to explore the parameter space of this model via many parallel, independent runs of the dynamics to find the best fit parameter values to the language data available.
Joshua B. Plotkin
University of Pennsylvania
Biology
Evolutionary Sciences
14
OSG Connect
190
duke-swcstaff
Duke Software Carpentry Workshop from Oct 27th to Oct 29th 2015
http://swc-osg-workshop.github.io/2015-10-27-duke/index.html
Mark R. DeLong
Duke University
Office of Information Technology
Multi-Science Community
15
Duke
769
UCSD_Libgober
Scraping Names off of FCC Exparte Meeting Logs
Brian Libgober
University of California, San Diego
School of Global Policy and Strategy
Social Sciences
14
OSG Connect
451
GRScorrelation
We calculate the autocorrelation merit factors for Golay-Shapiro-Rudin-like sequences and the crosscorrelation merit factors for pairs of such sequences. Each of the 2^n seed sequences of length n gives rise to an infinite family of sequences, and we have asymptotic formulas (see our preprint at arXiv: 1702.07697 [math.NT]) for the merit factors based on calculations involving only the seeds. The number of seeds grows exponentially, thus making this a project that is well-suited to distributed computing. We would like to extend Table 2 of our paper (minimum combined measure of autocorrelation and crosscorrelation, unconstrained search) to seeds of length 28. And we would like to extend Tables 1 and 3 of our paper (minimum autocorrelation and minimum combined measure among those sequences of minimum autocorrelation) to seeds of length 52, because we have a conjectue that something interesting may happen at length 52. We expect that the extension of T!
ables 1 and 3 will require about 130,000 runs, each of which would take about an hour each on a single thread of a typical workstation. And we expect that the extension of Table 2 will require about 45,000 runs taking about 45 minutes each in a similar situation.
Daniel J. Katz
California State University, Northridge
Mathematics
Mathematical Sciences
14
OSG Connect
1202193772
TG-BIO200038
RNAMake Science Gateway: a public resource for the design and analysis of RNA 3D structure for custom nanomachines
Joseph Yesselman
University of Nebraska-Lincoln
Chemistry
Biophysics
14
OSG Connect
281
atlas.org.utexas
ATLAS Connect team for University of Texas-Austin
Robert William Gardner Jr
University of Texas at Austin
Physics
High Energy Physics
16
ATLAS Connect
253
atlas.org.hamptonu
ATLAS Connect team for Hampton University
Robert William Gardner Jr
Hampton University
Physics
High Energy Physics
16
ATLAS Connect
438
GanForAuto
Test Case Generation For ADAS Validation Via Cycle GAN
Today’s automobile is equipped with a large amount of electronic circuits to achieve intelligent functions, such as collision avoidance, traffic sign detection, etc., for autonomous driving. To meet the safety standard, ensuring extremely small failure probability over all possible operation conditions is one of the critical tasks for an autonomous driving system. However, physically observing all these corner cases over a long time is almost impossible in practice. In this project, we use machine learning algorithms to efficiently generate corner cases that are not easy to observe.
Xin Li
Duke University
Electrical and Computer Engineering
Engineering
14
OSG Connect
617
CaseWestern_Tolbert
Structural Biology Related to HIV/EV-71
Blanton Tolbert
Case Western Reserve University
Chemistry
Structural Biology/Biophysics
14
OSG Connect
66
ExhaustiveSearch
ExhaustiveSearch (or ExSearch) is a machine learning application tuned to analyze class-labeled data using n-tuple feature vectors.
Sam Volchenboum
University of Chicago
Computation Institute
Bioinformatics
14
OSG Connect
448
glass
Glass problem is one of the outstanding unsolved problems in condensed matter physics. The exact solution of a model glass former in the limit of infinite spatial dimension exhibit a dynamical critical point. It is important to check the robustness of the resulting description under changing d for fundamental understanding. In this project we aim to take a closer look at this dynamical criticality as a function of spatial dimensions, using models of polydisperse hard sphere fluids. Computer simulation is an essential tool to pursue this study.
Patrick Charbonneau
Duke University
Chemistry
Computational Condensed Matter Physics
15
Duke
746
KentState_Strickland
Non-equilibrium dynamics of the quark-gluon plasma
Michael Strickland
Kent State University
Department of Physics
Physics
14
OSG Connect
369
PCFOSGUCSD
Work submitted as part of the physics computing facility (PCF) at the physics department at UCSD
Frank Wuerthwein
University of California, San Diego
Physics Department
Physics
4
UCSD
1321266094
CSM_BeEST
The Beryllium Electron capture in Superconducting Tunnel junctions Experiment (BEeST) employs the decay–momentum reconstruction technique to precisely measure the 7Be 7Li recoil energy spectrum in superconducting tunnel junctions (STJs). This approach is a powerful, model-independent method in the search for beyond SM scenarios since it relies only on the existence of a heavy neutrino admixture to the active neutrinos.
Kyle Leach
Colorado School of Mines
Physics
Physics
14
OSG Connect
224
cms.org.cornell
CMS Connect at Cornell University
Jim Alexander
Cornell University
Physics
High Energy Physics
18
CMS Connect
777
mwt2-staff
MWT2 staff - testing and monitoring
Robert William Gardner Jr
University of Chicago
Physics
Computer Science
14
OSG Connect
196984630
Michigan_Jahn
I want to make videos and documentation showing how to use the Open Science Grid to analyze large FreeSurfer datasets. This is to help make supercomputing resources more accessible to students and researchers at smaller colleges that may not have their own supercomputing cluster.
Andrew Jahn
University of Michigan
fMRI Laboratory
Biological and Biomedical Sciences
14
OSG Connect
805
Rice_Ogilvie
The ultimate goal is to train machine-learning-type models (e.g. GANs or CNNs) on DNA and RNA reads in order to classify both kinds of data into a common set of clusters. The application of this research is to improve our understanding of cancer development and progression by integrating single-cell genomic and transcriptomic data from the same patient. We plan on training these models on publicly available datasets that include both transcriptomic and genomic short reads, after first reducing those datasets to per-gene read counts.
Huw Ogilvie
Rice University
Department of Computer Science
Biological and Biomedical Sciences
14
OSG Connect
546
TG-MCB150001
Large-Scale Modeling of Macromolecular Binding Equilibria
Emilio Gallicchio
CUNY Brooklyn College
Chemistry
Chemistry
13
OSG-XSEDE
213
cms.org.ku
CMS Connect at The University of Kansas
Alice Bean
The University of Kansas
Physics
High Energy Physics
18
CMS Connect
293
atlas.wg.Monte-Carlo
ATLAS Connect team for Monte Carlo
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
508281087
TDAI_Staff
This project is for an XSEDE/Access Champions allocation, so there is no project that is planned for OSG presently. TDAI serves over 200 faculty affiliates that have interest in various aspects of Data Science, with researchers spanning disciplines from foundational methods, to applications in a variety of sciences, to data governance and policy. The intention of obtaining an OSG project is similar to other Champions accounts: to have resources readily available for researchers to test-drive against their workflow prior to obtaining their own allocations. https://tdai.osu.edu/research-action
Tanya Berger-Wolf
The Ohio State University
Translational Data Analytics Institute
Data Science
14
OSG Connect
1472383658
Michigan_Alben
The planned research will discover improved flows for thermal transport enhancement. We will extend an existing steady 2D method to efficiently compute optimal unsteady 2D flows in benchmark geometries such as channel flows, and closed and open domains between hot and cold surfaces. We will also develop computational methods for optimal flows in 3D domains that are analogous to the 2D domains we have studied, and determine the gains from 3D flows relative to 2D flows in comparable domains.
Silas Alben
University of Michigan
Mathematics
Applied Mathematics
14
OSG Connect
108
ContinuousIntegration
Provides continuous build and test services for OSG Connect via Jenkins.
Robert William Gardner Jr
University of Chicago
Computation Institute
Technology
14
OSG Connect
363689105
UCSD_Guiang
Improve performance of data downsampling tools for future LHC runs
Jonathan Guiang
University of California, San Diego
Physics
Physics
14
OSG Connect
581956816
Arkansas_UITSStaff
Research computing staff at University of Arkansas https://directory.uark.edu/departmental/uits/university-information-technology-serv
Don DuRousseau
University of Arkansas
Information Technology
Research Computing
14
OSG Connect
488
DUNE
Project entry corresponding to the DUNE VO.
Thomas Robert Junk
DUNE
N/A
High Energy Physics
9
Fermilab
287
atlas.wg.E-Gamma
ATLAS Connect team for E Gamma
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
570977624
GATech_Lang
Use a 3D thermal model to invert thermochronometer data for constraining the subsurface orientation and slip history of faults, exhumation of landscapes and sedimentation of basins.
Karl Lang
Georgia Institute of Technology
EAS
Earth Science
14
OSG Connect
333
Perchlorate
Assessment of costs and environmental impacts of drinking water technologies for the removal of perchlorate
Justin M Hutchison
University of Illinois
Civil and Environmental Engineering
Engineering
14
OSG Connect
147
TG-MCB140232
A longstanding goal of molecular simulations is to accurately predict the three-dimensional fold of a biopolymer given only knowledge of its primary sequence. Although recent work has demonstrated the successful folding of proteins ranging from 10-80 amino acids from the unfolded state, no comparable results exist for the folding of structured RNAs. In recent work, we have shown that this is a result of underlying inaccuracies in the energy model itself, due to underlying assumptions that work well for describing amino acids but are inapplicable for describing nucleic acids in solution. We have systematically corrected these biases in order to more accurately capture the inherent flexibility of single-stranded RNA loops, accurate base stacking energetics, and purine anti-syn interconversions. In a departure from traditional quantum chemistry-centric parameterization schemes, we calibrate the molecular mechanics potentials directly against the relevant thermodynamic and kinetic measurements of aqueous nucleosides and nucleotides. This application is to continue the kinetic, thermodynamic characterization of improved RNA force-field to enable de-novo RNA folding.
Alan Chen
State University of New York at Albany
Chemistry
Molecular and Structural Biosciences
13
OSG-XSEDE
1522370732
NMSU_Lawson
I am requesting an OSPool project for my postdoctoral research investigating drivers of population decline for the American Kestrel, a raptor species that breeds across North America. I plan to use OSG resources to compile my environmental data and fit statistical models.
Abigail Lawson
New Mexico State University
Fish, Wildlife, and Conservation Ecology
Ecological and Environmental Sciences
591
UCI_McnLab
Looking at widefield calcium imaging data from different brain regions
Bruce McNaughton
University of California, Irvine
Neurobiology and Behavior
Neuroscience
14
OSG Connect
498
plantGRN
With the emergence of massively parallel sequencing, genome-wide expression data production has reached an unprecedented level. This abundance of data has greatly facilitated maize research, but may not be amenable to traditional analysis techniques that were optimized for other data types. Using publicly available data, a Gene Co-expression Network (GCN) can be constructed and used for gene function prediction, candidate gene selection and improving understanding of regulatory pathways. Several GCN studies have been done in maize, mostly using microarray datasets. To build an optimal GCN from plant materials RNA-Seq data, parameters for expression data normalization and network inference were evaluated. We previously constructed an optimized gene coexpression network for maize. In this project, we want to build gene regulatory networks for Arabidopsis, rice maize, and sorghum.
Karen McGinnis
Florida State University
Biological Science
Bioinformatics
14
OSG Connect
631
UWMadison_Vavilov
Research group of Maxim Vavilov
Maxim Vavilov
University of Wisconsin-Madison
Physics
Physics
14
OSG Connect
102
GRASP
Atomic structure calculations based on multiconfiguration Dirac–Hartree–Fock theory utilizing Grasp2k, a general-purpose relativistic atomic structure package.
Richard Irving
University of Toledo
Physics
Physics and astronomy
14
OSG Connect
431
nEXO
The nEXO experiment aims to search for double
beta decay of Xenon-136.
Raymond Tsang
Pacific Northwest National Laboratory
National Security Directorate
High Energy Physics
14
OSG Connect
181
peers
This is an analysis of statewide data for all students in grades K-2. The aim of the analysis is to examine the effects of peers' achievement and composition effects on individual student achievement. This analysis requires mixed-effect modeling and quantile regression. R, and qrLMM package, will be used for analysis, 19 instances of analysis (one for each quantile .05 to .95 in .05 increments) will be conducted for each grade (k, 1, and 2). Each data set is less than 1GB, but requires approximately 6gb to run.
Jessica Sidler Folsom
Florida State University
Florida Center for Reading Research
Ecological and Environmental Sciences
14
OSG Connect
1944794325
ND_Chen
Training AI models on public medical image data
Danny Chen
University of Notre Dame
College of Engineering
Engineering
643
NeuroscienceGateway
Neuroscience Gateway (NSG)
Amit Majumdar
University of California, San Diego
San Diego Supercomputing Center
Neuroscience
14
OSG Connect
1342269514
UTEP_Moore
We are developing portable containers for deep-learning frameworks and applications
Shirley Moore
University of Texas at El Paso
Computer Science
Computer and Information Services
134
TG-MCB130135
Meta-genomics and Cancer research data
Ashok Mudgapalli
University of Nebraska Medical Center
Research IT Office
Mathematical Sciences
13
OSG-XSEDE
759
CampusWorkshop_Feb2021
accounts for Feb 8 2021 campus workshop
Christina Koch
University of Wisconsin-Madison
Computer Sciences
Training
14
OSG Connect
306
PTMC
We are applying Monte Carlo particle transport codes to proton therapy treatment planning with the goal of reducing the uncertainty in the proton beam range in patient.
Derek Dolney
University of Pennsylvania
Radiation Oncology
Molecular and Structural Biosciences
14
OSG Connect
1179045082
UCLA_OARC
Office of advanced computing center staff at UCLA
Tajendra Vir Singh
University of California, Los Angeles
OARK
Computer Science
14
OSG Connect
290
atlas.wg.Higgs
ATLAS Connect team for Higgs
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
1902734420
Utah_Nelson
Monte Carlo research for the simulation of radiation transport for applications in medicine. Will be looking at proton therapy applications specifically using the Geant4 wrapper, TOPAS.
Nicholas Nelson
University of Utah
Department of Radiation Oncology
Physics and radiation therapy
819
UWMadison_Dopfer
Real-Time Estimation and Forecasting of COVID-19 Cases and Hospitalizations
Doerte Doepfer
University of Wisconsin-Madison
Medical Sciences
Health
14
OSG Connect
587
osg.Ceser
Infrastructure Testing
Frank Wuerthwein
University of California, San Diego
Physics
Multidisciplinary
14
OSG Connect
4
UMich
To use a systems biology approach to directly and significantly impact our understanding and treatment of tuberculosis.
Paul Wolberg
University of Michigan
Microbiology and Immunology
Microbiology
30
OSG
481
GPCRbinders
Computational design of protein-based affinity reagents capable of binding to GPCRs and inducing an agonized or antagonize state, or binding in a function-independent manner.
Christopher Bahl
Institute for Protein Innovation
Biology
Biological Sciences
14
OSG Connect
388
srccoding
Studying coding schemes for lossy source compression under privacy constraints
Joerg Kliewer
New Jersey Institute of Technology
Electronic Engineering
Computer and Information Science and Engineering
14
OSG Connect
119
LIGO
Gravitational Wave Astronomy
Peter F. Couvares
International Gravitational-Wave Observatory Network (IGWN)
Physics
Gravitational Physics
14
OSG Connect
674
TG-DMS190036
Modeling Random Directions and Simplex Transformations
Rayleigh Lei
University of Michigan
Statistics
Statistics and Probability
13
OSG-XSEDE
384
holosim
simulations of population genetics in 2d landscapes
Allan Strand
College of Charleston
Biology
Evolutionary Sciences
14
OSG Connect
1231382541
AllenISD_Cheon
High school science fair project
Jimin Cheon
Allen Independent School District
Biology
Computer and Information Sciences
14
OSG Connect
806
OSGUserTrainingPilot
User training
Christina Koch
Open Science Grid
OSGConnect
Training
14
OSG Connect
275
atlas.org.umass
ATLAS Connect team for University of Massachusetts
Robert William Gardner Jr
University of Massachusetts
Physics
High Energy Physics
16
ATLAS Connect
301
AnimalSocialNetworks
Project Name: Animal Social Networks
Short Project Name: AnimalSocialNetworks
Field of Science: Ecology
Field of Science (if Other):
PI Name: Erol Akcay
PI Email: eakcay@sas.upenn.edu
PI Organization: University of Pennsylvania
PI Department: Biology
Join Date: Nov 30th 2015
Sponsor: OSG Connect
OSG Sponsor Contact: Bala
Project Contact: Amiyaal Ilany
Project Contact Email: amiyaal@sas.upenn.edu
Telephone Number:
Project Description: Modeling the formation and dynamics of animal social networks, and how these dynamics affect phenomena at the individual and population levels
Erol Akcay
University of Pennsylvania
Biology
Biological Sciences
14
OSG Connect
70
TG-DEB140008
We propose to test community level population genetic patterns of coral reef fishes as they pertain to the Depth Refuge Hypothesis (DRH) of coral reefs by applying a statistical framework for multi-species analyses using hierarchical Approximate Bayesian Computation (hABC). The DRH specifies that deep reefs are protected from disturbances that effect shallow habitat and can provide a viable reproductive source for shallow reef areas following disturbance. It has been proposed that these foundation reefs may provide refuge not only from local disturbances such as storms or pollution, but can act as a refuge for geographically broad scale major disturbances such as the glaceoeustatic sea-level fluctuations that occur on the order of approximately 100k years at an amplitude of over 100m. During the Last Glacial Maximum (LGM) sea level was thought to have reduced shallow habitat by as much as 90% in the tropical Pacific possibly resulting in increased habitat fragmentation, local extinction, or bottlenecks. We will combine multi-taxa population genetic datasets into a single analysis to determine the proportion of the current community that historically expanded in a temporally clustered pulse, when the pulse occurred, and in what direction (i.e. from shallow water to shallow water across locations, deep water to adjacent shallow water, from shallow water to adjacent deep water, or deep water to deep water across locations.) across the Hawaiian archipelago.
Robert Toonen
University of Hawaii at Manoa
Unknown
Biological Sciences
13
OSG-XSEDE
776
UTAustin_Zimmerman
Gravitational waves and black holes
Aaron Zimmerman
University of Texas at Austin
Physics
Gravitational Physics
14
OSG Connect
Other
CHTC-XD-SUBMIT
UChicago_OSGConnect_login04
UChicago_OSGConnect_login05
TACC-Stampede2
GravSearches
80
UCSDPhysAstroExp
Experimental Astrophysics from UCSD supported users
Frank Wuerthwein
University of California, San Diego
Physics
Astrophysics
4
UCSD
241
TG-MCB150090
Solvation strongly affects the structures and properties of molecules. Molecular simulations for many problems in chemistry, physics, and biology require an accurate depiction of solvation, and the most ubiquitous and important solvent is water. Yet, water is difficult to model in molecular simulations - fast but sometimes erroneous modeling can be done with continuum solvent models, or relatively accurate but expensive modeling can be done explicitly. Users must generally compromise accuracy and efficiency for the problem of interest. Though widespread efforts are directed at testing water models, much of this work is duplicative and incomplete. Here we propose extensive computer simulations of biomolecular solvation using XSEDE. These simulations will provide a systematic database of solvation free energies for a large and diverse set of biomolecules and conformations. This database will extend our understanding of molecular solvation and will provide a communal resource for the development of continuum solvent models, a focus of many groups throughout the field.
Emiliano Brini
State University of New York at Stony Brook
Laufer Center
Molecular and Structural Biosciences
13
OSG-XSEDE
515
CatalystHTVS
Using high throughput computing to screen molecular catalysts for energy fuel conversion based on experimental database or in-silico generated structures. In the next stage, the output from HTC calculations will be used to train machine learning models to allow faster and higher throughput molecular catalyst design.
Heather J. Kulik
Massachusetts Institute of Technology
Chemical Engineering
Physical Chemistry
14
OSG Connect
733
Cornell_Lai
Scalable and reproducible bioinformatics through the Galaxy platform
William KM Lai
Cornell University
Molecular Biology and Genetics
Biological Sciences
14
OSG Connect
188
EHEC
Project Description: Our research is primarily focused on the transmission and evolution of two zoonotic pathogens, enterohemorrhagic Escherichia coli (EHEC) and Salmonella. These pathogens reside in the intestinal tracts of animal hosts where they encounter diverse microbial communities, fluctuating nutrient levels, and myriad host factors. Transmission between hosts requires these pathogens to survive varied environmental conditions. The general stress protection system (regulated by the alternative sigma factor, σs) is known to play a central role in environmental persistence and transmission. Acid and desiccation tolerance are two transmission-associated phenotypes that are dependent upon σs –regulated genes. We are also investigating the role of prophage in fitness. EHEC harbor multiple lambda-like prophage and cryptic phage remnants in their genome that facilitate genomic rearrangements, gene duplications, and deletions by homologous recombination.
We are investigating how these phage-mediated genomic rearrangements influence the persistence of EHEC in its bovine host and the environment. The goals of our research are to use results from these fundamental studies in the development of strategies to reduce pathogen transmission.
Chuck Kaspar
University of Wisconsin-Madison
Bacteriology
Microbiology
14
OSG Connect
524
retrovision
Simulation of the retrospective Bayesian model for visual perception and working memory published in PNAS, to create a mechanistic model for the aforementioned probabilistic framework
Ning Qian
Columbia University
Zuckerman Institute
Neuroscience
14
OSG Connect
200
cms.org.ucla
CMS Connect at Universify of California, Los Angeles
Jay Hauser
University of California, Los Angeles
Physics
High Energy Physics
18
CMS Connect
704
UCDavis_Pickett
Computational survey and analysis of superconducting hydrides at high pressure
Warren E. Pickett
University of California, Davis
Physics
Materials Science
14
OSG Connect
692
TexasAM_Fang
A General Framework for Inference on Shape Restrictions
Zheng Fang
Texas A&M University
Economics
Economics
14
OSG Connect
2107736775
ETHZ_Zhang
To make machine learning techniques widely accessible.
Ce Zhang
ETH Zurich
Computer Science
Computer Science
14
OSG Connect
274
atlas.org.uiowa
ATLAS Connect team for University of Iowa
Robert William Gardner Jr
University of Iowa
Physics
High Energy Physics
16
ATLAS Connect
1915351942
UNL_Ramamurthy
Research on optimizing large data transfers for science experiments
Byrav Ramamurthy
University of Nebraska-Lincoln
School of Computing
Computer and Information Services
664
UCDenver_Butler
Data-Consistent Approaches for Uncertainty Quantification
Troy Butler
University of Colorado Denver
Mathematical and Statistical Sciences
Mathematics
14
OSG Connect
807
UIowa_Reno
Developing a mission-independent neutrino & lepton simulation/propagation package
Mary Hall Reno
University of Iowa
Physics & Astronomy
Astronomy
14
OSG Connect
1639234221
MSSM_Ali
Hands on Training on Robust Molecular Simulations Introduces students to the exciting areas in Computational Biophysics, drug design, bioinformatics and potentially other computing intensive fields
Rejwan Ali
Icahn School of Medicine at Mount Sinai
Neurology
Biological and Biomedical Sciences
14
OSG Connect
1296704977
WichitaState_Hwang
Analysis of porous media using pore-scale simulations of additively manufactured wicks with X-ray computed tomography.
Gisuk Hwang
Wichita State University
Department of Mechanical Engineering
Mechanical Engineering
14
OSG Connect
365
FRISpoilageProject
We are using the Mothur pipeline to clean and analyze 16S rRNA gene sequences collected from sous vide vegetables that were held under refrigeration until the onset of spoilage. (Goal- To identify microorganisms responsible for spoilage in sous vide processed vegetables)
Chuck Kaspar
University of Wisconsin-Madison
Microbiology
Microbiology
14
OSG Connect
226
cms.org.utk
CMS Connect at University of Tennessee
Stefan Spanier
University of Tennessee
Physics
High Energy Physics
18
CMS Connect
411
sykclusters
DMRG simulation of many body fermion system
John McGreevy
University of California, San Diego
Physics
Physics
14
OSG Connect
676
UWMadison_Rebel
Project for Brian Rebel high energy physics group from UW-Madison
Brian Rebel
University of Wisconsin-Madison
Physics
Physics
14
OSG Connect
458
OTPCand0vbb
PSEC group at the University of Chicago is developing Large-Area Picosecond Photo-Detectors (LAPPDs). By reconstructing the arrival position and time of photons produced in water or liquid scintillator on highly segmented fast photo-detectors such as LAPPDs one can reconstruct tracks by using the `drift time' of photons, much as one does
with electrons in a Time Projection Chamber. We are developing new event reconstruction techniques for large water and liquid scintillator detectors. For example see A. Elagin et al., “Separating Double-Beta Decay Events from Solar Neutrino Interactions in a Kiloton-Scale Liquid Scintillator Detector by Fast Timing”, Nucl. Instr. Meth. Phys. Res. A849 (2017) 102.
Henry Frisch
University of Chicago
Physics
High Energy Physics
14
OSG Connect
636
UCSD_Rappel
Biophysics simulations
Wouter-Jan Rappel
University of California, San Diego
Physics
Physics
14
OSG Connect
447
QuantEvol
Simulations of evolution of quantitative characters in finite populations
Shripad Tuljapurkar
Stanford University
Biology
Biological Sciences
14
OSG Connect
440
StSNE
Find low dimensional representation of the high dimensional data
Yichen Cheng
Georgia State University
Institute for Insight
Statistics
14
OSG Connect
528
ExoplanetaryACS
In this project, the absorption cross section (or molecular opacity) and important exoplanetary atmospheric molecules will be generated.
Michael R. Line
Arizona State University
School of Earth and Space Exploration
Astrophysics
14
OSG Connect
785
Arizona_Males
Data Analysis for Exoplanet Direct Imaging
Jared Males
University of Arizona
Department of Astronomy and Steward Observatory
Astronomy
14
OSG Connect
318
duke-boolnet
Experimental Boolean networks built on FPGAs, with the purpose of studying the fundamental dynamical properties of complex
Daniel Gauthier
Duke University
Physics
Physics
15
Duke
539
brainlifeio
Neuroscience is engaging at the forefront of science by dissolving disciplinary boundaries and promoting transdisciplinary research. This process can facilitate discovery by convergent efforts from theoretical, experimental and cognitive neuroscience, as well as computer science and engineering.
Franco Pestilli
Indiana University
Psychological and Brain Sciences
Neuroscience
14
OSG Connect
1732585414
UCSD_Politis
Bootstrap hypothesis testing methods for time series - we are trying to compute the rejection probabilities of our hypothesis testing method as a measure of their efficacy. This requires generating several samples of time series for a given sample size and hyperparameter specification and running our test repeatedly to compute the empirical rejection probability. This is done over several sample sizes and hyperparameter specs.
Dimitris N Politis
University of California, San Diego
Department of Mathematics
Mathematics and Statistics
315
TPOT
Project Description: TPOT is an open source Python tool that automatically creates and optimizes Machine Learning pipelines using genetic programming. GitHub repo: http://github.com/rhiever/tpot
Jason H. Moore
University of Pennsylvania
Institute for Biomedical Informatics
Bioinformatics
14
OSG Connect
1677287435
ePIC
the ePIC collaboration based out of the EIC
John Lajoie
Brookhaven National Laboratory
Physics
Nuclear Physics
139
EIC
519
TG-PHY180007
The Jet Energy-loss Tomography with a Statistically and Computationally Advanced Program Envelope (JETSCAPE) collaboration is an NSF funded SSI-collaboration of 6 institutions.The JETSCAPE Collaboration is tasked with the design and construction of a software framework that can be used to simulate collisions of large nuclei at extreme energies, to populate the framework with interacting modules that simulate different aspects of the collision, and use Bayesian techniques to make statistical comparisons between the results of this event generator and experimental data. Nuclear collision experiments at Brookhaven National Lab. and at CERN produce a state of matter called the Quark Gluon Plasma (QGP), which exists only above 2 trillion degrees. The QGP lives for about 10 septillionths of a second, before cooling down and explosively evaporating to a spray of conventional matter. The separate modules of the JETSCAPE event generator will simulate the initial state of the colliding nuclei, the pre-equilibrium dynamics, the viscous fluid dynamical expansion where the QGP cools down to an interacting state of conventional matter, and the final evaporation of the droplet into a spray of conventional particles. The framework and developed event generator places special emphasis on the simulation of extremely high energy jets that are produced in rarer events, traverse the dense QGP and are modified on exit. The study of this modification in comparison with jets in vacuum yields clues to the internal structure of the QGP. Before such simulations can be carried out, the different interacting modules of the event generator have to be tuned (unknown parameters set) by comparison with a small subset of available experimental data. We are requesting allocation time on the OSG to start the tuning of a scaled down version of the full event generator. The startup allocation will allow us to estimate both the time required for the tuning and simulations of the default event generator.
Abhijit Majumder
Wayne State University
Physics And Astronomy
Nuclear Physics
13
OSG-XSEDE
944567874
USDA_Andorf
The research is part of the Maize Genetics and Genomics Database (MaizeGD) to utilize protein structure models to improve maize functional genomics. The project will generate new protein structure models to improve functional classification, canonical isoform detection, gene structure annotation, and assigning confidence scores to point mutations based on the likelihood to change function.
Carson Andorf
United States Department of Agriculture
Midwest Area, Corn Insects, and Crop Genetics Research Unit
Biological and Biomedical Sciences
558
TG-DMR180127
Campus Champion for Arizona State University
Sirong Lu
Arizona State University
Research Computing
Materials Research
13
OSG-XSEDE
559
BCH_ResearchComputing
Facilitation of Boston Children's Hospital Researchers on OSG Connect
Arash Nemati Hayati
Boston Children's Hospital
Medical Sciences
14
OSG Connect
745
Mines_GomezGualdron
Prediction of Adsorption in Metal-Organic Frameworks
Diego Gomez-Gualdron
Colorado School of Mines
Chemical and Biological Engineering
Chemical Engineering
14
OSG Connect
1267980677
UNL_Hebets
Assess spider web structure by training and tracking models using SLEAP
Eileen Hebets
University of Nebraska-Lincoln
Biological Sciences
Biological Sciences
38
TG-DMR130036
We request high throughput computing resources to perform diagrammatic Monte Carlo calculations of strongly correlated non-equilibrium electron systems. The calculations employ existing implementations of real-time quantum Monte Carlo algorithms for the solution of quantum impurity models, which have been tested and benchmarked; they also involve extensions to these algorithms which are currently under development. We will use these codes to address two types of physics problems: strongly correlated lattice systems treated within the dynamical mean field approximation, and exact properties of model systems for mesoscopic and molecular electronic junctions.
Emanuel Gull
University of Michigan
Physics
Materials Science
13
OSG-XSEDE
595
GATech_Chau
Attention Shift Visualization
Polo Chau
Georgia Institute of Technology
Computer Science and Engineering
Computer Science
14
OSG Connect
216
cms.org.bu
CMS Connect at Boston University
Jim Rohlf
Boston University
Physics
High Energy Physics
18
CMS Connect
46
TG-MCB130072
This allocation will be used to help MSU users transition from local HPC resources to XEDE resrouces
Benjamin Ong
Michigan State University
Institute for Cyber Enabled Research
Mathematical Sciences
13
OSG-XSEDE
132
TG-DMR140072
When bulk helium-4 is cooled below T = 2.18 K, it undergoes a thermodynamic phase transition to a superfluid, characterized by zero viscosity and quantization of flow. The superfluid state of matter is a macroscopic manifestation of quantum mechanics, as it can be described by a single complex wave function with a phase that does not depend on position. The phase coherence can be probed in a container filled with helium-4, by reducing one or more of its dimensions until they are smaller than the coherence length; the spatial distance over which order propagates. As this dimensional reduction occurs, enhanced thermal and quantum fluctuations push the transition to the superfluid state to lower temperatures. However, this trend can be countered via the proximity effect, where a bulk 3D superfluid is coupled to a low (2D) dimensional superfluid via a weak link producing superfluid correlations in the film at temperatures above the Kosterlitz-Thouless temperature. Recent experiments probing the coupling between 3D and 2D superfluid helium-4 have uncovered an anomalously large proximity effect, leading to an enhanced superfluid density that cannot be explained using the correlation length alone.We intend to explore the microscopic origin of this enhanced proximity effect via large scale quantum Monte Carlo simulations of helium-4 in a topologically non-trivial geometry that incorporates the important aspects of the experiments. We will modify, test and deploy our research group's home-built high performance worm algorithm path integral quantum Monte Carlo code (http://code.delmaestro.org) at low temperatures with an eye toward improving efficiency through enhanced parallelization and hybridization.
Adrian Del Maestro
University of Vermont
Physics
Materials Science
13
OSG-XSEDE
327
TG-MCB140088
The molecules of life are large, complex machines that drive the operations of the cell. Modeling the atomic structure and underlying dynamics of these molecules is critical for understanding disease and developing therapeutics. Recent advances in experimental instrumentation and scientific software have have made high resolution biological structures more accessible than ever, but large data volumes and complex calculation often require extensive computation. Cryo-electron microscopy (Cryo-EM), for example, can now reveal structures from heterogeneous biological samples to atomic resolution - better than 3 angstroms. These structures require terabytes of experimental data and upwards of 20,000 hours of compute time for accurate determinations to be made. X-ray crystallography, the workhorse of structural biology, can now combine complex computational modeling algorithms like Rosetta with experimental data to arrive at a complete structure determination, which may require more than 1000 hours of compute time. Drug discovery efforts have embraced computational “virtual screening’ to filter the most likely targets from vast drug fragment libraries by combining computational chemistry and experimentally-determined molecular structures. In these screens, the only limit to the number of drug candidates screened is computational time. Finally, molecular dynamics simulations give insight into the motions biological molecules adopt as they perform their jobs, but also require high-performance computing resources for meaningful results. As a Campus Champion at Harvard Medical School and SBGrid, I support the research computing needs of a diverse structural biology community and XSEDE is an essential resource in driving this critical research.
Jason Key
Harvard Medical School
BCMP / SBGrid
Molecular and Structural Biosciences
13
OSG-XSEDE
99280644
BYUI_Becerril
Training undergraduate students in scientific computing through teaching elective courses
Héctor A. Becerril
Brigham Young University Idaho
Chemistry Department
Chemistry
14
OSG Connect
922683276
UOregon_Melgar
Conducting earthquake simulations as part of a larger collaboration (https://github.com/Marcus-Adair/Accelerating-Data-Intensive-Seismic-Research-Through-Parallel-Workflow-Optimization-and-Federated-CI). Planning to eventually run some ML for graph neural network GNSS denoising."
Diego Melgar
University of Oregon
Cascadia Region Earthquake Science Center
Geological and Earth Sciences
164
Teamcore
Solving large scale Partially Observable Markov Decision Processes (POMDPs) in order to discover efficient health intervention mechanisms which will assist in prevention of HIV spread amongst homeless youth in Los Angeles.
Amulya Yadav
University of Southern California
Computer Science
Computer and Information Science and Engineering
9
ISI
334
POLARBEAR
The evolution of the universe is based on the idea of gravitational instability, whereby initial tiny fluctuations in the density of the Universe grew under the influence of gravity to form the large-scale gravitational structures we see around us today. These structures bend the trajectories of Cosmic Microwave Background photons through gravitational lensing, distorting its primordial polarization and converting divergent polarization patterns (E-modes) into curled polarization patterns (B-Modes). Imaging the lensing-generated B-modes, the POLARBEAR telescope will be able to shed light on all the components of the Universe influencing structure formation, such as neutrino mass and dark energy.
Brian Keating
University of California, San Diego
Physics
Astrophysics
14
OSG Connect
386
TG-IRI160006
Staff allocation to support the mission of the XSEDE Community Infrastructure (XCI) team comprised of the RACD and XCRI groups to facilitate interaction, sharing, compatibility, campus integration and SP Coordination of all relevant software and related services across the national CI community building on and improving on the foundational efforts of XSEDE.
Victor Hazlewood
National Institute for Computational Sciences
None
Information, Robotics, and Intelligent Systems
13
OSG-XSEDE
1706931595
NCSU_Petersen
Annealing of graphite by using large ensembles to accelerate barrier crossing times. https://www.sciencedirect.com/science/article/pii/S0022311517315490
Andrew Petersen
North Carolina State University
OIT HPC
Materials Science
14
OSG Connect
368
SFCphases
Molecular-scale interaction between mobile and stationary
phases as they relate to supercritical fluid chromatography
(SFC) is modeled with hybrid Monte Carlo methods. Carbon dioxide is the main component of the mobile phase in SFC, which typically operates above the critical point. Simulations use seven mole percent methanol in the mobile phase. The objective of the proposed work is understanding the interaction between mobile-phase molecules and the alkylsilane-coated silica stationary phase. The computational method is Monte Carlo simulation. Hybrid molecular dynamics moves explore conformations of eighteen-carbon alkylsilane chains bonded to silica substrate.
Paul Siders
University of Minnesota Duluth
Chemistry and Biochemistry
Chemistry
14
OSG Connect
126
boostconf
Project for data sharing and analysis of boosted object physics and jet phenomenology for topics discussed in the BOOST Conference Series
David Wilkins Miller
University of Chicago
Physics
High Energy Physics
14
OSG Connect
220
cms.org.umn
CMS Connect at University of Minnesota
Roger Rusack
University of Minnesota
Physics
High Energy Physics
18
CMS Connect
496
dynamo
Equilibrium dynamical models are useful tools for inferring the mass distribution of galaxies and determining the amount and structure of their dark matter halos. The goal of this work is to explore degeneracies in the modeling of elliptical galaxies to evaluate how well we can understand properties such as their dark matter density distribution, the mass-to-light ratio of their stellar populations, and the orbital anisotropy of various tracer populations.
Asher Wasserman
University of California, Santa Cruz
Astronomy and Astrophysics
Astrophysics
14
OSG Connect
786
UChicago_Jonas
Developing machine learning techniques for chemical spectroscopy
Eric Jonas
University of Chicago
Computer Science
Chemistry
14
OSG Connect
181412983
GSU_ARCTIC
https://arctic.gsu.edu/
Suranga Edirisinghe
Georgia State University
Advanced Research Computing Technology and Innovation Core
Research Computing
714
USD_RCG
Supporting and enabling research at the University of South Dakota.
Ryan Johnson
University of South Dakota
Information Technology Services
Computer and Information Sciences
14
OSG Connect
156
cgl
We use machine learning to look for complex epistatic interactions associated with disease risk. Website: http://www.epistasis.org
Jason H. Moore
University of Pennsylvania
Biostatistics and Epidemiology
Biological Sciences
14
OSG Connect
1478585217
IIT_Li
Develop Lagrangian particle methods for moving interface problems in fluid mechanics and materials science; Develop Physical Informed Neural network (PINN) for Green function-based methods.
Shuwang Li
Illinois Institute of Technology
Applied Mathematics
Materials Science
285
atlas.wg.B-Physics
ATLAS Connect team for B Physics
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
681
duke.lsst
Large Synoptic Survey Telescope at Duke
Steven Kahn
Duke University
Physics
Astronomy
15
Duke
699
UCSD_Elman
Identifying genetic and biological subtypes of Alzheimer’s disease
Jeremy Elman
University of California, San Diego
Psychiatry
Biology
14
OSG Connect
1775745695
TG-IRI160007
The mission of the XSEDE Cyberinfrastructure Integration (XCI) team is to facilitate interaction, sharing and compatibility of all relevant software and related services across the national CI community building on and improving on the foundational efforts of XSEDE. We need access to XSEDE resources for periodic testing of new software releases.
Richard Knepper
Cornell University
Center for Advanced Computing
Applied Computer Science
14
OSG Connect
221
cms.org.olemiss
CMS Connect at University of Mississipi
Lucien Cremaldi
University of Mississipi
Physics
High Energy Physics
18
CMS Connect
387
TG-MCB160192
Proteins custom-designed for specific molecular function have great promise to advance many areas of science and industry. High throughput methods – in particular, effective computational modeling of structure and function – are necessary to identify proteins with novel functions out of the vast number of candidate protein sequences. Nevertheless, state-of-the-art methods have only limited accuracy in predicting the functional impact of even a few mutations.
To improve models for functional proteins, we are developing methods within the Rosetta computational protein design software suite that represent subtle structural fluctuations using flexible-backbone ensembles and integrate multiple functional constraints on proteins (i.e. catalytic conformations or binding partners). Promising initial results demonstrated improvement over standard fixed-backbone approaches in initial tests against large curated mutational datasets for experimentally determined binding affinities and high-throughput screening of protein-protein interactions.
Our approach of using discrete ensembles to model flexible and dynamic systems is well suited to the distributed nature of high performance computing clusters. Our goal of predicting the functional effect of defined sequences is likewise well suited. In particular, the Open Science Grid will be very useful for our high-processing, low-memory requirements. The purpose of this Startup request is two-fold: benchmarking and optimizing computational methodologies to model functional proteins. First, we will streamline our methodology for XSEDE in preparation for a Research allocation application. Second, additional computing resources from XSEDE will greatly expand our ability develop methodology beyond the limitations of benchmarking on the computational resources at our home institution.
Samuel Thompson
University of California, San Francisco
Bioengineering and Therapeutics
Molecular and Structural Biosciences
13
OSG-XSEDE
540
CloudTemplate
Cloud Custom Template for Non-Experts
Prasad Calyam
University of Missouri-Columbia
Electrical Engineering and Computer Science
Computer Science
14
OSG Connect
630561480
UCSD_McGreevy
We are studying chiral states on a lattice system
John McGreevy
University of California, San Diego
Physics
Physics
14
OSG Connect
781
TG-CHE200122
Development of machine learning models for molecular simulations
The development of fast, accurate, and universal empirical potentials (EP) has been at the forefront of computational chemistry for many decades due to the high cost and bad scaling of accurate quantum mechanical (QM) methods and the low accuracy of more efficient classical force fields. The central goal of our project is bridging the speed and accuracy gap between these two approaches with machine-learning (ML) potentials. ML potentials have proven their ability to predict energies and other properties of molecules when trained on properly developed data sets. While these potentials are fast and accurate, the majority do not aim to become universal in their description of chemical interactions. This limits their use to only specific molecular systems or bulk materials. Our group developed probably the first universal ML atomistic potentials ANI-1x and ANI-2x for organic molecules containing CHNOSFCl atoms. Apart from other similar efforts in quantum chemistry and materials science, this neural network potential was shown to be transferable across different chemical environments, generalizing to the density-functional theory (DFT) level of accuracy on a large set of organic molecules while being six orders of magnitude faster.
One of the main challenges with developing highly accurate and transferable ML potential is the construction of training and test datasets. We developed a fully automated approach for the generation of datasets with the intent of training universal ML potentials based on active learning (AL) techniques. AL reduces the training set size by up to 90% data required compared to naive random sampling techniques. Even with the AL technique employed, the dataset size required to train accurate and transferable ML potential is in the range of millions of conformers of small molecules (up to about 20 non-hydrogen atoms). We ended up with a dataset size of 5M molecular conformations for CHNO elements (ANI-1x), and an additional 5M data points to parametrize potential for SFCl elements (ANI-2x).
Our goal in this project is to utilize a High-Throughput Computing (HTC) model to run a very large number of relatively small quantum-chemical calculations in order to build new datasets set for a subsequent training of neural network models. All calculations are orchestrated as a Manager-Worker application that distributes a massive number of tasks to workers using the Python RQ library. We plan to use a single Access Point provided by the HTCondor Software Suite (HTCSS) and operated by the Open Science Grid to host the Manager of the application and to deploy the workers across the XSEDE facilities and the OSPool.
Olexandr Isayev
Carnegie-Mellon University
Chemistry
Chemical Sciences
13
OSG-XSEDE
XRAC
CHTC-XD-SUBMIT
CHTC-ap40
SDSC-Expanse
cwr109
Other
CHTC-XD-SUBMIT
CHTC-ap40
TACC-Frontera
CHE20009
659
COVID19_Illinois_Gammie
The goal of this project is to predict and assess the effect of epidemic intervention strategies for the State of Illinois. Our effort includes a group of covid-19 modelers at the University of Illinois at Urbana-Champaign that includes faculty members Charles Gammie, Nigel Goldenfeld, and Sergei Maslin and graduate students George Wong and Zach Weiner. We are one of the groups providing advice to the office of Governor Pritzker and to our local public health district.
Charles Gammie
University of Illinois Urbana-Champaign
Physics
Health
14
OSG Connect
862327868
UCDavis_Yarov-Yarovoy
https://health.ucdavis.edu/physiology/faculty/yarovoy.html
Vladimir Yarov-Yarovoy
University of California, Davis
Physiology and Membrane Biology
Computational Biology
14
OSG Connect
545
TG-DMS180031
Robust policy gradient improvement across multiple embodied morphologies
Thomas Merkh
University of California, Los Angeles
Mathematics
Applied Mathematics
13
OSG-XSEDE
751070568
TG-BIO210164
The project aims to build a dataset of bioelectrical dynamics of a simulated cluster of somatic cells. Bioelectric patterns in tissue are now known to be a critical instructive influence over embryonic and regenerative morphogenesis, as well as over conversion to cancer.
Michael Levin
Tufts University
Biology
Cell Biology
14
OSG Connect
109
duke-WaterCrystal
Water structure in protein crystals
Patrick Charbonneau
Duke University
Chemistry
Biochemistry
15
Duke
931875864
UAF_Aschwanden
Generate a physically-consistent state-estimate—a reanalysis—of the Greenland Ice Sheet (GrIS) from 1980 to 2020
Andy Aschwanden
University of Alaska Fairbanks
Snow, Ice and Permafrost
Geological and Earth Sciences
14
OSG Connect
1406503170
NOAA_Vincent
General research into improvement of fisheries stock assessment methods.
Matthew Vincent
National Oceanic and Atmospheric Administration
Southeast Fisheries Science Beaufort Lab
Natural Resources and Conservation
14
OSG Connect
354
EvoProtDrug
Little is known about the evolutionary pathways enabling a protein to change its function to changing environmental needs, especially in regards to metabolism and toxicity. Evolution simulations that explicitly model the three-dimensional interaction of mutated proteins with their targets is a new approach that complements the ongoing explosion of directed evolution experiments. In this project, the evolutionary dynamics of a lattice representation of antibiotic resistance protein (beta lactamase) is studied by enhanced-sampling folding-binding simulations for an initial protein undergoing selection-dependent mutation to bind a new antibiotic. The goals of this work are to understand the fundamental physical bottlenecks and dynamical behavior of protein evolution. Important questions include the extent of dominant pathways (convergent evolution) and phase transitions in evolutionary rates (punctuated equilibrium). These principals and their structural underpinnings can also be used to inform rational design of antibiotics that exploit bottlenecks in pathogen mutational response.
Milo Lin
UT Southwestern
Green Center for Systems Biology
Biophysics
14
OSG Connect
1124125707
LLNL_Sochat
Developer tooling, including environments, apps, and workflows.
Vanessa Sochat
Lawrence Livermore National Laboratory
Livermore Computing (lc)
Computer and Information Services
14
OSG Connect
200044350
TG-PHY220009
Conduct particle resolved simulations of prolate spheroids in viscoelastic and EVP fluids using an in-house finite difference solver.
Donald L Koch
Cornell University
Department of Chemical and Biomolecular Engineering
Chemical Engineering
14
OSG Connect
118
TG-TRA130007
This is a renewal request for the Campus Champion allocation for Northwest Missouri State University.
David Monismith
Northwest Missouri State University
Mathematics, Computer Science, and Information Systems
Training
13
OSG-XSEDE
23
GlassySystems
Studies of static and dynamic properties of glassy systems.
See also: http://www.columbia.edu/cu/chemistry/groups/reichman/
The dynamics and static properties of glassy systems can be studied in great detail by simple model systems, either those on a lattice or those consisting of mixtures of spherical particles. In order to do that, one can use any many techniques generally under the umbrella of Monte Carlo Sampling or Molecular Dynamics. In order to get detailed properties, is is often advantageous or necessary to run a large number of independent simulations, and to calculate properties averaged over these simulations. It may also be necessary to study these systems with a range of parameter values, e.g. temperature or system size. Hence, this problem lends itself well to high throughput computing, at least for cases where the individual simulations comprising a workflow are not too long.
David Reichman
Columbia University
Chemistry
Chemistry
14
OSG Connect
2079313771
JacksonLab_Awe
This study aims to develop a reusable pipeline to screen for IEMs using genomic data.
Olaitan Awe
Jackson Laboratory for Genomic Medicine
Computational Research Facilitation
Bioengineering & Biomedical Engineering
14
OSG Connect
233
cms.org.brown
CMS Connect at Brown University
Meenakshi Narain
Brown University
Physics
High Energy Physics
18
CMS Connect
366
idTrackerParallel
Running the idTracker software (http://www.idtracker.es/) in parallel on OSG.
Andrew Ruether
Swarthmore College
ITS
Evolutionary Sciences
14
OSG Connect
799
CSUSB_ITS
Group for CSUSB staff supporting research computing.
Dung Vu
California State University, San Bernadino
Information Technology
Computer Sciences
14
OSG Connect
20
ConnectTrain
OSG user training activity.
Christina Koch
Open Science Grid
Research Facilitation
Training
14
OSG Connect
841996560
CSUN_Jiang
Wildfire Prediction for California using various remote sensing data from the past decades. This is a computation intensive research project that involves applying machine learning models for data analysis and prediction, and also computation-intensive work for data visualization. This project will involve collaborations from both internal and external students at California State University, Northridge.
Xunfei Jiang
California State University, Northridge
Computer Science
Computer and Information Sciences
282
atlas.org.washington
ATLAS Connect team for University of Washington
Robert William Gardner Jr
University of Washington
Physics
High Energy Physics
16
ATLAS Connect
342
TrappedOrbits
Computing a bunch of orbits in a disk galaxy in the presence of a spiral arm. The aim is to identify trapped orbits and determine the physical parameters that determine the rate of scattering out of trapped orbits.
Kathryne J Daniel
Bryn Mawr College
Physics
Astrophysics
14
OSG Connect
596
UCF_Bennett
DFT Calculations
Christopher Bennett
University of Central Florida
Physics/Planetary Science
Physics
14
OSG Connect
322
BakerLab
Protein folding
David Baker
University of Washington
Molecular Engineering and Sciences
Molecular and Structural Biosciences
30
OSG
740
RIT_ResearchComputing
Research Computing staff at the Rochester Institute of Technology (RIT).
Kirk Anne
Rochester Institute of Technology
RIT Research Computing
Computer and Information Sciences
14
OSG Connect
788
Michigan_Wells
Training neural networks for particle physics research
James Wells
University of Michigan
Physics
Physics
14
OSG Connect
284
atlas.org.yale
ATLAS Connect team for Yale University
Robert William Gardner Jr
Yale University
Physics
High Energy Physics
16
ATLAS Connect
457
Diffpred
Modelling and simulation of diffusion magnetic resonance images (dMRI) using white matter tract mapping information
Franco Pestilli
Indiana University
Neuroscience
Neuroscience
14
OSG Connect
608
Yale_RYang
Network Resource Abstraction and Optimization for Large-Scale Scientific Workflow
Richard Yang
Yale University
Department of Computer Science
Computer and Information Services
14
OSG Connect
32
UNC-RESOLVE-photometry
Astronomy image manipulation
David Stark
UNC Chapel Hill
Department of Physics and Astronomy
Physics and astronomy
30
OSG
782903564
GATech_Coogan
We are attempting to run a simulation for Georgia Tech's Robotarium on our website when users upload run files. Our simulator is based on https://github.com/robotarium/robotarium_python_simulator , with edits to certain functions.
Samuel Coogan
Georgia Institute of Technology
Electrical and Computer Engineering
Electrical, Electronic, and Communications
14
OSG Connect
533
steward
Steward Observatory Data Analytics
Chi-Kwan Chan
University of Arizona
Astronomy
Astronomy
14
OSG Connect
1193659107
Michigan_Schwarz
Work on Di-Higgs searches, specifically HH->bbtautau process, and my main research focus is working on Machine learning algorithm optimization for the analysis, see link of my most recent progress of my research: https://cernbox.cern.ch/index.php/s/qPJ7QkOcOjrZdMW
Thomas Schwarz
University of Michigan
Physics
Physics, Particle Physics, High Energy Physics
14
OSG Connect
362
SysBioEdu
A project for teaching analysis of large data sets for construction of models (i.e. graphs) of biological systems.
Stephen Ficklin
Washington State University
Horticulture
Biological and Critical Systems
14
OSG Connect
661
COVID19_FoldingAtHome
Folding at Home for COVID-19, on the Open Science Grid https://foldingathome.org/covid19/
Greg Bowman
Folding@Home Consortium (FAHC)
Biochemistry
Biochemistry
14
OSG Connect
201
cms.org.ucr
CMS Connect at University of California, Riverside
Gail Hanson
University of California, Riverside
Physics
High Energy Physics
18
CMS Connect
484
UHITSACI
A project to help get users from UH onto open science grid.
Sean Cleveland
University of Hawaii
Cyberinfrastructure
Computer and Information Science and Engineering
14
OSG Connect
710
Tutorial-PEARC20
PEARC20 tutorial
Mats Rynge
Open Science Grid
OSGConnect
Computer and Information Science and Engineering
14
OSG Connect
1407748521
UTK_Luettgau
Piloting the National Science Data Fabric, A Platform Agnostic Testbed for Democratizing Data Delivery
Jakob Luettgau
University of Tennessee, Knoxville
Electrical Engineering & Computer Science
Computer and Information Science and Engineering
14
OSG Connect
347
NeurOscillation
Our lab studies the rhythms of the brain, recorded electrically as oscillations in voltage. These brain rhythms have been hypothesized to underlie functional communication between different brain regions, but the mechanism by which it does this is not clear. Additionally, it is not clear from a biophysical standpoint how these oscillations are generated. Our lab studies both noninvasive and clinical recordings from human subjects and patients in order to better understand these rhythms of the brain. For example, the project contact's personal research investigates the variations in the waveform shape of neural oscillations. Why are some oscillations nonsinusoidal (e.g. sawtooth), how does this impact neural communication, and how does this relate to high-level behaviors?
Bradley Voytek
University of California, San Diego
Cognitive Science
Neuroscience
14
OSG Connect
1984311722
TG-TRA180011
Allocations to help UD clients understand what resources can potentially be available to them to extend and/or complement UDs local HPC resources. Our goal is to apply for startup or other types of allocations for clients without necessarily using the Campus Champion resource, and/or provide clients with access to one of the resources, like Bridges, via the workshops to get a sense of resources and then apply for their own allocation. These allocations will be offered as an option to our UD clients to experiment in anticipation of applying for their own allocations.
Anita Schwartz
University of Delaware
CS&S
Other Engineering and Technologies
14
OSG Connect
626
Pitt_Koes
Deep Learning for Drug Discovery
David Ryan Koes
University of Pittsburgh
Department of Computational and Systems Biology
Physical Chemistry
14
OSG Connect
563
SINGE
SINGE uses Granger Causality tests to infer gene regulatory networks from pseudotemporally ordered single-cell transcriptomic data.
Anthony Gitter
University of Wisconsin-Madison
Biostatistics and Medical Informatics
Bioinformatics
14
OSG Connect
603
Hawaii_Gorham
Monte Carlo simulations for The Antarctic Impulsive Transient Antenna (ANITA) project. ANITA is a NASA-funded long-duration stratospheric balloon experiment designed to detect ultra-high energy neutrinos and cosmic rays through wideband radio emission from particle showers in the ice and atmosphere.
Peter W. Gorham
University of Hawaii at Manoa
Astrophysics
Computer and Information Services
14
OSG Connect
708
Stanford_Zia
Dynamic simulation of colloidal glass transition
Roseanna Zia
Stanford University
Chemical Engineering
Engineering
14
OSG Connect
1134002200
Dartmouth_Chaboyer
Computational stellar models are widely used in astrophysics and are often consulted to interpret observations of starlight. My research group aims to improve stellar models by incorporating updated physics into the models, creating a database of stellar models for use by other researchers, and to use these improved stellar models to study a variety of issues related to galactic archelogy and the formation of galaxies. https://stellar.host.dartmouth.edu
Brian Chaboyer
Dartmouth College
Physics and Astronomy
Astronomy and Astrophysics
363
HCCLocalSubmit
Jobs from our clusters that flock to the OSG
Derek Weitzel
University of Nebraska
Holland Computing Center
Community Grid
67
HCC
526
EICpseudodata
Monte Carlo simulations of particle production in the set-up corresponding to the kinematics of observables, which are planned to be measured in the future US-based Electron Ion Collider facility.
Vladimir Khachatryan
State University of New York at Stony Brook
Department of Physics and Astronomy
Nuclear Physics
14
OSG Connect
564
FIFE
Project entry corresponding to FIFE experiments within the Fermilab VO.
Ken Herner
Fermilab
N/A
High Energy Physics
9
Fermilab
439
SimPrily
This project is for anyone using SimPrily to perform demographic simulations.
Ariella Gladstein
University of Arizona
Ecology and Evolutionary Biology
Evolutionary Sciences
14
OSG Connect
583
SDCC
Project entry for the BNL Scientific Data & Computing Center
John Steven De Stefano Jr.
Brookhaven National Laboratory
N/A
Computer and Information Science and Engineering
114
BNL
629
ASU_Singharoy
Computational Immunology
Abhishek Singharoy
Arizona State University
School of Molecular Sciences
Biological and Biomedical Sciences
14
OSG Connect
1498730645
Webster_Suo
This work aims to construct a flexible scan system using multiple cameras that can correctly reconstruct 3D objects -- a human face with expression. The work proposed and used mathematical models to automate the 3D object reconstruction.
Xiaoyuan Suo
Webster University
Computer and information science
Computer Science
703
UWMadison_Paskewitz
Training neural networks to classify images of ticks
Susan Paskewitz
University of Wisconsin-Madison
Entomology
Biological Sciences
14
OSG Connect
464
Fluka
FLUKA Monte Carlo calculations
Sunil Chitra
Brookhaven National Laboratory
Physics
Physics
14
OSG Connect
621
Arcadia_Curotto
Computational chemistry of hydrogen-nanoparticle interactions and n-alkane conformer transitions
Emanuele Curotto
Arcadia University
Chemistry
Chemistry
14
OSG Connect
633
BC_Savage
IT and Research Computing at Boston College
Brian Savage
Boston College
Information Technology Services
Computer Science
14
OSG Connect
312
IBN130001-Plus
Child project of TG-IBN130001
Donald Krieger
University of Pittsburgh
Neurosurgery
Neuroscience
13
OSG-XSEDE
61
P0-LBNE
LBNE will endeavor to perform precision measurements of key parameters pertaining to neutrino oscillations, advancing our understanding of some of the most fundamental issues in particle physics, such as neutrino mass hierarchy, nucleon decay and a few other others. The Software and Computing Organization of LBNE is tasked with providing core infrastructure for its Physics Tools development and data processing, which will need to accommodate the needs of a diverse and distributed research organization.
Maxim Potekhin
Brookhaven National Laboratory
Physics
High Energy Physics
30
OSG
28
BioStat
Bioinformatics and biostatistics for genetic risk factors at the Duke Medical Center.
Janice McCarthy
Duke University
Medical Center
Bioinformatics
14
OSG Connect
512
TG-MCB190187
Eco-Evolutionary Feedback and Dynamics in the Long-Term E. coli Evolution Experiment
Joao Ascensao
University of California, Berkeley
Bioengineering
Genetics and Nucleic Acids
13
OSG-XSEDE
222
cms.org.princeton
CMS Connect at Princeton University
Dan Marlow
Princeton University
Physics
High Energy Physics
18
CMS Connect
522
FEMyo
Using FEM and multi-parametric design to perform mechanical simulations of metamaterial structures for the purpose of mechanical characterization. These structures will subsequently be screened for use as a myocardial support device.
Kevin Costa
Icahn School of Medicine at Mount Sinai
Cardiology
Biomedical research
14
OSG Connect
489
SeaQuest
Project entry corresponding to the SeaQuest VO. This is purely for job accounting purposes.
David Christian
SeaQuest
N/A
Nuclear Physics
9
Fermilab
557
TG-DMR160157
Numerical Study of Disordered Periodically Driven Criticality
William Berdanier
University of California, Berkeley
Physics
Condensed Matter Physics
13
OSG-XSEDE
1243866024
Arizona_Chan_Steward
Scalable astronomical data analytics for the Department of Astronomy and Steward Observatory at the University of Arizona
Chi-kwan Chan
University of Arizona
Department of Astronomy and Steward Observatory
Physics
390
duke-EfficientScore
We will benchmark various algorithms to benchmark the efficient score.
Konosuke Iwamoto
Duke University
Biostatistics
Statistics
15
Duke
157
Phylogenomics
The project entails the sequencing and assembly of the transcriptomes of 100+ non-model tree species from the USA and China. This information is then used to infer a functional phylogenomic tree from which inferences regarding functional similarity and species co-existence and diversity are drawn.
Nathan G Swenson
University of Maryland
Department of Biology
Bioinformatics
14
OSG Connect
191
ERVmodels
Project Description: Endogenous retroviruses (ERVs) are viewed as ancient retroviral infections in vertebrate genomes and are commonly referred to as viral fossils, accounting for approximately 8% of the human genome. In order to increase our understanding of these viruses in host genomes, I am developing more complex models that describe the evolution of ERVs in host genomes. Specifically, I am interested in understanding evolutionary patterns of ERVs that have intact genes and are theoretically able to re-infect when
compared to those that lost this ability.
Fabricia Nascimento
University of Oxford
Department of Zoology
Zoology
14
OSG Connect
415
ddpscbioinfo
The Donald Danforth Plant Science Center Bioinformatics project tracks Open Science Grid computing usage by Danforth Center researchers. Bioinformatics research at the Danforth Center largely focuses on plant genomics (genome sequencing, genetic analysis, transcript profiling, etc.) and high-throughput phenotyping (image analysis, genotype-phenotype association analysis, etc.).
Noah Fahlgren
Donald Danforth Plant Science Center
Bioinformatics
Plant Biology
14
OSG Connect
64
HL-LHC-TP
Simulate hundreds of millions of high-energy proton proton collisions, which mimic the collisions expected at a potential High Luminosity LHC. This simulated data will be used to assess the performance of potential CMS detector upgrades, for inclusion in a Technical Proposal.
Meenakshi Narain
Brown University
Physics
High Energy Physics
30
OSG
619
QCArchive_Smith
The compute will be used for community facing data. This will include generating data for open AI datasets and computing molecules for undergraduate education.
Daniel G. A. Smith
Virginia Tech University
Molecular Sciences Software Institute
Physical Chemistry
14
OSG Connect
532
BiostatsChapple
Bayesian Clinical Trials
Andrew Chapple
LSU School of Public Health
Biostatistics
Statistics
14
OSG Connect
675
WayneStateU_Pruneau
Simulations of heavy-ion collisions with Hydrodynamics
Claude Pruneau
Wayne State University
Physics and Astronomy
Physics
14
OSG Connect
714693215
UConn_Zhu
GERS Laboratory working on big earth observation data and environmental change
Zhe Zhu
University of Connecticut
Department of Natural Resources and the Environment
Earth and Ocean Sciences
14
OSG Connect
30
NRELMatDB
Ab initio calculation of the physical properties of 10^4 to 10^6 materials, database of results, and web site for access.
Peter Graf
National Renewable Energy Laboratory
Computational Science Center
Materials Science
14
OSG Connect
335
PRTH
Modeling of Monte Carlo simulations (Geant4) in order to test many different parameters (collimator and shielding size, irradiation angles...) to define the best design for new medical nuclear treatment devices
Endre Takacs
Clemson University
Astronomy and Physics
Physics
14
OSG Connect
651
Guam_Bentlage
Marine science bioinformatics - analyzing phylogenetic trees, blasting sequences, read mapping
Bastian Bentlage
University of Guam
Marine Laboratory
Biological Sciences
14
OSG Connect
756
Stanford_Das
RNA tertiary structure of COVID-19 UTRs as therapeutic and vaccine targets: https://daslab.stanford.edu/news
Rhiju Das
Stanford University
Biochemistry
Biological and Biomedical Sciences
14
OSG Connect
400
ClusterJob
ClusterJob is a project for 'painless massive computational experiments'. Visit www.clusterjob.org
Hatef Monajemi
Stanford University
Statistics
Computer and Information Science and Engineering
14
OSG Connect
302
SWITCHHawaii
We are using the SWITCH power system planning model to design power systems for Hawaii that have minimal expected cost across a wide range of future fossil fuel prices.
Matthias Fripp
University of Hawaii at Manoa
Electrical Engineering
Engineering
14
OSG Connect
644
UW_deKok
NLP for business narratives
Ties de Kok
University of Washington
Economics
Economics
14
OSG Connect
300
hABCNWHI
Hierarchical Approximate Bayesian Computation to Detect Community Response to Sea Level Change in the Hawaiian Archipelago.
Methods that integrate population sampling from multiple taxa into a single analysis are a much needed addition to the comparative phylogeographic toolkit. Here we present a statistical framework for multi-species analysis based on hierarchical approximate Bayesian computation (hABC) for inferring community dynamics and concerted demographic response. Detecting community response to climate change is an important issue with regards to how species have and will react to past and future events. Furthermore, whether species responded individualistically or in concert is at the center of related questions about the abiotic and biotic determinants of community assembly. This method combines multi-taxon genetic datasets into a single analysis to determine the proportion of a contemporary community that historically expanded in a temporally clustered pulse as well as when the pulse occurred. We will apply this method to 59 species in the Hawaiian Archip ela! go in order to examine community response of coral reef taxa to sea-level change in Hawaii. The method can accommodate dataset heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and utilizes borrowing strength from the simultaneous analysis of multiple species. This hABC framework used in a multi-taxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently, and can be used with a wide variety of comparative phylogeographic datasets as biota-wide DNA barcoding data sets accumulate.
Yvonne Chan
Iolani School
Biology
Biological Sciences
14
OSG Connect
314
TG-PHY160001
XSEDE resources will be used to generate several trillion simulated collision events for the CERN Large Hadron Collider Experiment. The simulated events will be generated by the Monte Carlo simulation program called Herwig 7 (herwig.hepforge.org) interfaced with the module HJets++ (hjets.hepforge.org). The primary focus will the simulation of the scattering of two protons into a Higgs boson is association with jets (H+3 Jets). Jets are are clusters of energetic hadrons. Hadrons are composite particles that are comprised of fundamental particles called quarks and gluons. Results for the next-to-next leading order QCD corrections of H+3 Jets have been published in Physical Review Letters (http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.111.211802). However, further simulations are required to evaluate the theoretical uncertainties for the integrated scattering cross-section and kinematics distributions for H+3 Jets. In order to evaluate the scattering cross-section with a Monte Carlo integration error of 1 per mille, it is necessary to simulate at least a trillion weighted events. The parallel computing computing environment that XSEDE provides will provide the necessary events to achieve lower integration errors.
Terrance Figy
Wichita State University
Mathematica, Statistics, and Physics
Physics
13
OSG-XSEDE
179
xenon1t
The XENON Dark Matter Experiment located at the Gran Sasso Laboratories (INFN, Italy), is currently the leader world project searching for the so called Dark Matter, something which is completely different from ordinary matter. This Dark Matter is not (as the name hints) visible, but it should pervade the entire Universe. Its presence has been confirmed by different experimental evidences, however its intrinsic nature is one of the big puzzle of Modern Physics. The XENON Experiment could reveal the nature of the DM looking at the possible interactions of the DM with ordinary matter, for instance with the Xenon, a noble gas been liquified at very low temperature. The study of the background signal, from the environment and from the materials that make up the new detector containing the Xenon (which is currently under construction and called XENON1T), is essential to understand the detector's behavior and its implications on its performances. For this purpose an extensive Montecarlo simulation and study is needed, and this require quite a lot of CPU time. The MC simulation of the XENON experiment is based on the open source codes called GEANT4 and ROOT.
Luca Grandi
University of Chicago
Physics
Astrophysics
14
OSG Connect
XRAC
UChicago_OSGConnect_login05
SDSC-Expanse
chi135
553
TG-TRA170047
Campus Champion for North Dakota State University
Nicholas Dusek
North Dakota State University
Center for Computationally Assisted Science and Technology
Training
13
OSG-XSEDE
332
TG-TRA140029
The immediate purpose of this request is to have small allocations available for showcasing and quick access to a variety of XSEDE resources. Long term goals are to encourage and assist campus users in applying for their own allocations.
Scott Hampton
University of Notre Dame
Center for Research Computing
Other
13
OSG-XSEDE
770
Michigan_Bioinformatics
OSG for UMich Bioinformatics
Chris Gates
University of Michigan
Biomedical Research Core Facilities
Biological and Biomedical Sciences
14
OSG Connect
103
BioMolMach
The molecular machines associated with biological membranes are particularly remarkable. Membrane-associated proteins play an essential role in controlling the bidirectional flow of material and information, and as such, they are truly devices able to accomplish complex tasks. These include ion channels, transporters, pumps, receptors, kinases, and phosphatases.
These proteins, like any machine, need to change shape and visit many conformational states to perform their function. Our project is aimed at gaining a deep mechanistic perspective of such protein function, linking structure to dynamics, by characterizing the free energy landscape that governs the key functional motions.
Benoit Roux
University of Chicago
Biology
Molecular and Structural Biosciences
14
OSG Connect
486
Fermilab
Project entry corresponding to Fermilab VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
320
AMS
Monte Carlo simulation for the AMS experiment
Baosong Shan
Massachusetts Institute of Technology
LNS
Particle Physics
30
OSG
128
TG-CHE140110
Monte Carlo molecular simulation together with a coarse-grained model is used to study the single-stranded to double-stranded transition in DNA both in solution and with one strand bound to a surface. Representing DNA microarrays, hybridization on a surface is studied and the effect of surface density, strand length and sequence homology on duplex stability is investigated. Results can better inform empirical surface hybridization models.
John Stubbs
University of New England
Chemistry and Physics
Chemistry
13
OSG-XSEDE
1480334498
CaseWestern_Zhang
A project involving neuroimaging and genetics data for neurodegenerative disease.
Lijun Zhang
Case Western Reserve University
Dept. of Population & Quantitative Health Sciences (PQHS)
Biological and Biomedical Sciences
14
OSG Connect
693
Tufts_Hempstead
Tufts Computer Architecture Lab
Mark Hempstead
Tufts University
Electrical & Computer Engineering
Computer Architecture/Computer Engineering
14
OSG Connect
194
PegasusTraining
Project used for Pegasus tutorials and training
Mats Rynge
University of Southern California
ISI
Training
9
ISI
778
NYU_Fund
Economics of telecommunications networks
Fraida Fund
New York University
Electrical and Computer Engineering
Electrical, Electronic, and Communications Engineering
14
OSG Connect
1824766561
SalemState_Poitevin
Find segments of nucleotides in different genomes that can be parsed both visually and phonetically.
Pedro Poitevin
Salem State University
Department of Mathematics
Visual Arts
14
OSG Connect
260
atlas.org.msu
ATLAS Connect team for Michigan State University
Robert William Gardner Jr
Michigan State University
Physics
High Energy Physics
16
ATLAS Connect
833
Mines_BeEST
The Beryllium Electron capture in Superconducting Tunnel junctions Experiment (BEeST) employs the decay–momentum reconstruction technique to precisely measure the 7Be 7Li recoil energy spectrum in superconducting tunnel junctions (STJs).
Kyle Leach
Colorado School of Mines
Physics
Physics
14
OSG Connect
325
atlas.wg.USAtlas-TechSupport
Atlas Connect training project
Robert William Gardner Jr
University of Chicago
Computation Institute
High Energy Physics
16
ATLAS Connect
34400913
Arizona_DataScienceInstitute
Helps researchers and graduate students, to learn Data Science Tools over a wide available computational resources in order to enhance their research capabilities.
Nirav Merchant
University of Arizona
Data Science Institute
Data Science
14
OSG Connect
780
UConn_Zhang
Graph-based clustering method with application to single-cell RNA-seq data from human pancreatic islets
Yuping Zhang
University of Connecticut
Department of Statistics
Mathmatics and Statistics
14
OSG Connect
782
ACE_NIAID
Includes the study of biology using computational techniques and the creation of tools that work on biological data. Also includes the effective use of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making to improve human health. A variety of applications, including drug discovery & design using Monte Carlo simulations and evolutionary biology with mutual information calculations. Also genomics and medical imaging analysis.
Darrell Hurt
National Institute of Allergy and Infectious Diseases
Office of Cyber Infrastructure and Computational Biology
Bioinformatics
14
OSG Connect
709
UNC_Drut
Computational Quantum Matter at Finite Temperature
Joaquin Drut
University of North Carolina at Chapel Hill
Department of Physics and Astronomy
Physics
14
OSG Connect
4446861
MSKCC_Chodera
We are developing a system to enable high throughput free energy calculations.
John Chodera
Memorial Sloan Kettering Cancer Center
MSKCC
Bioinformatics
308
duke-SWC-Duke15
Training Workshop
Mark R. DeLong
University of Chicago
Computation Institute
Multi-Science Community
15
Duke
399
TG-AST170008
The outer solar system has been a topic of intense scientific research for twenty-five years, but particularly within the past year. In January 2016, astronomers Mike Brown and Konstantin Batygin announced ``Planet Nine'' -- a hypothetical 10 Earth-mass object in the distant solar system responsible for the statistically significant orbital clustering of the longest-period trans-Neptunian objects (TNOs). Since this announcement, several more long-period TNOs have been discovered. Our specific research focus is studying the orbital dynamics of these objects, both absent of and in the presence of a Planet Nine, with the ultimate goal of determining the mostly likely orbit of a potential Planet Nine. Such a study requires numerical N-body simulations of hundreds of ``clones'' of each object, where a clone is produced by varying the orbital elements of an object within uncertainties. These simulations must encompass the entirety of the solar system's history after the formation of the planets, or approximately 4.5 billion years. Additionally, we must conduct these simulations for a suite of potential Planet Nines, further increasing the computational demand. We intend to ascertain which simulations, and therefore which configurations of Planet Nine, allow for the dynamical survival and force the orbital alignment of the longest period TNOs. The computational demand for these simulations far exceeds what is available to us on a laptop or desktop computer, and therefore we are requesting a Startup allocation on OSG to complete this work.
Stephanie Hamilton
University of Michigan
Physics
Astrophysics
13
OSG-XSEDE
58
duke-4fermion
We are performing a lattice field theory calculation of a 2 flavor fermion model with a four fermion interaction. We look for critical behavior at strong coupling.
Shailesh Chandrasekharan
Duke University
Physics Department
High Energy Physics
15
Duke
754
PRP
Machine Learning HTCondor submission from PRP Nautilus
Tom DeFanti
Pacific Research Platform
Pacific Research Platform
Machine Learning/AI
14
OSG Connect
755
LSUHSC_Yu
Bayesian Mediation Analysis
Qingzhao Yu
Louisiana State University Health Sciences Center
Biostatistics
Health Sciences
14
OSG Connect
645
Mizzou_OSGTeaching
Teaching OSG at Mizzou
Timothy Middelkoop
University of Missouri
Research Computing Support Services, Division of IT
Education
14
OSG Connect
217
cms.org.mit
CMS Connect at Massachusetts Institute of Technology
Christoph Paus
Massachusetts Institute of Technology
Physics
High Energy Physics
18
CMS Connect
1829007221
TG-CIS210126
Statistical analysis on keys generated by a lattice based cryptography algorithm for post-quantum cryptography to determine patterns in the types of errors produced in the keys.
Alexander Nelson
University of Arkansas
Computer Science & Computer Engineering
Computer Science
14
OSG Connect
239
cms.org.vanderbilt
CMS Connect at Vanderbilt University
Will Johns
Vanderbilt University
Physics
High Energy Physics
18
CMS Connect
412
KORDrugdiscov
It has been shown that deregulation of the Kappa Opioid Receptor (KOR) can contribute to drug abuse and other psychiatric disorders. Therefore, KOR agonists/antagonists have become a target for the development of pharmacotherapies for the treatment of addiction and other CNS disorders. Unfortunately, few chemical scaffolds have been shown to bind selectively to the KOR. Through the use of computational methods, we will screen a variety of chemical scaffolds to see how well they bind to the active pocket of the KOR and Mu Opioid Receptor. From these results, we will identify targets with high binding affinity to Kappa and low binding affinity to Mu. The identified compounds will then be screened for in vitro binding affinity to identify novel KOR selective ligands.
David Toth
Centre College
Chemistry
Chemistry
14
OSG Connect
144
cms.org.colorado
CMS Connect project for University of Colorado
Douglas Johnson
University of Colorado Boulder
Physics
High Energy Physics
18
CMS Connect
1420515722
Columbia_Mandal
Recent experiments demonstrated that by placing a molecule inside an optical cavity one can modify ground state chemical reactivity. It has been observed that when molecular vibrations are strongly coupled to the quantized radiation field inside an optical cavity, the chemical kinetics is suppressed. The theoretical understanding of such remarkable effects remains elusive. In this work, a quantum dynamics approach for simulating the vibration-cavity (Vibro-Polaritons) hybrid system will be developed.
Arkajit Mandal
Columbia University
Department of Chemistry
Chemistry
14
OSG Connect
555
TG-CHE170021
Exact solutions of the Schrodinger equation for the helium atom
Shengli Zou
University of Central Florida
Chemistry
Physical Chemistry
13
OSG-XSEDE
339
poromech
In order to reduce carbon dioxide emissions, experts have proposed requiring major carbon dioxide emitters to modify their infrastructure to collect carbon dioxide exhaust and compress it into a super-critical fluid for injection into a well-sealed geologic structure such as an exhausted oil or natural gas reservoir. We are therefore developing a tool to assess and monitor potential carbon capture and storage sites.
We use large-scale reservoir simulations to investigate the mechanical stresses that would effect a reservoir as it is injected with super-critical carbon dioxide. Since we will not know the precise geologic structure of a given field site, this requires us to run a very large number of computationally-intensive simulations (10$^4$-10$^7$) in order to adequately investigate every possible geologic structure. These simulations can then be compared to measurements from the surface and from wells drilled into the reservoir, allowing us to identify which proposed structures best explain the data. This will allow us to infer the structure and state of the subsurface.
Stephen Moysey
Clemson University
Environmental Engineering and Earth Sciences
Ecological and Environmental Sciences
14
OSG Connect
790
Rowan_Rasool
Machine learning algorithm robustness study
Ghulam Rasool
Rowan University
Electrical and Computer Engineering
Computer Sciences
14
OSG Connect
1968105797
UCF_Zou
Using computational tools to investigate properties of materials.
Shengli Zou
University of Central Florida
Department of Chemistry
Chemistry
14
OSG Connect
456
cms.org.baylor
CMS Connect at Baylor University
Kenichi Hatakeyama
Baylor University
Physics
High Energy Physics
18
CMS Connect
404
evolmarinva
Our group uses genomic tools to understand the evolutionary process of marine invasions.
Erik Sotka
College of Charleston
Department of Biology
Evolutionary Sciences
14
OSG Connect
401
macsSwigmodels
Every individual’s genome carries within it the history of all the ancestors of that individual. Thus, by analyzing a small number of genomes, we can accurately infer the demographic history of entire human populations. This demographic history helps establish a baseline that is needed for research and discovery in medical genomics.
We are using a process to more accurately infer the demographic history of human populations by comparing genomic statistics from millions of genome simulations to real population genomic data. While other researchers have worked with this process using only a few individuals or a portion of a chromosome, we are pushing the limit of computing capabilities by simulating whole chromosomes of hundreds of individuals. Using the whole chromosome allows us to look at more recent demographic history, which is particularly helpful in finding genetic links to disease processes. After publication, we will make our pipeline available so other researchers can apply it to other populations.
This project pushes the frontier of genomic research in that it uses new methods, simulates a larger part of the genome, and is being applied to populations not yet thoroughly studied.
Ariella Gladstein
University of Arizona
Ecology and Evolutionary Biology
Evolutionary Sciences
14
OSG Connect
383
Groundhog
Define spatio-temporal High Gamma activity patterns in the human neocortex during waking, and compare them to the observed activity in preceding/subsequent sleeps to see whether specific waking patterns recur during sleep.
Eric Halgren
University of California, San Diego
School of Medicine
Neuroscience
14
OSG Connect
326564611
Emory_Pesavento
The goal of our research project is to develop a new technique to estimate impulse response functions in Time-varying-parameters vector autoregressive models (in short: TVP-VARs). TVP-VARs are particularly useful because, unlike traditional VAR models, they accounts for changing economic conditions by allowing parameters to change over time. Estimating impulse responses (one of the main tools in macroeconomic analysis) in a TVP-VAR requires the implementation of Markov Chain Montecarlo algorithms (such as Gibbs sampling). This is a computationally demanding task in a TVP-VAR framework, due to the huge number of parameters to estimate. However, we could substantially ease such task by using parallel computing techniques. In this way, we could provide policy makers with a more realistic and flexible framework use to perform macroeconomic policy evaluation."
Elena Pesavento
Emory University
Economics
Economics
21
EvoTheory
Linkage disequilibrium's contribution to the maintenance of sexual reproduction
Though sexual reproduction is nearly ubiquitous in nature, its costs are substantial. Foremost among these costs are the twofold cost of males and the cost of destroying successful genetic associations. Understanding the paradox of the persistence of sex despite these detriments is a central question in evolutionary theory. In order to persist regardless of these disadvantages, the benefits of sexual reproduction must be substantial - offspring of sexual reproduction must have at least twice the fitness of asexual clones. The most generalizable hypotheses addressing the benefits of sex propose that genetic drift increases linkage disequilibrium, creating a surfeit of genomes with intermediate fitness. Sexual recombination eliminates linkage disequilibrium, thereby increasing genetic variation for fitness and improving the efficiency of natural selection. However, previous research using this framework has failed to address the biological reality of interactions between genes. Because the cost of destroying beneficial genetic interactions is one of the major costs of sex, this cannot be overlooked. In this work, I use a computational gene network model in which genes interact and genetic interactions evolve to investigate the hypothesis that linkage disequilibrium decreases the fitness and adaptability of asexual populations. I test this both by evolving artificial organisms in conditions that will increase linkage disequilibrium, and by evolving them in an environment with a shifting optimum, which will make linkage disequilibrium more costly.
I am running a python script that runs populations of artificial gene networks (numerical matrices) through repeated rounds (on the order of 10s of thousands) of mutation, selection and reproduction, analyzing the evolutionary dynamics of these populations, and storing the data generated by this in text files.
Christina Burch
University of North Carolina at Chapel Hill
Biology
Evolutionary Sciences
14
OSG Connect
137
TG-MCB140211
Why would a genotypically homogeneous population of cells live to different ages? We propose a mathematical model of cellular aging based on gene interaction network. This model network is made of only non-aging components, and interactions among genes are inherently stochastic. Death of a cell occurs in the model when an essential gene loses all of its interactions. The key characteristic of aging, the exponential increase of mortality rate over time, can arise from this model network with non-aging components. Hence, cellular aging is an emergent property of this model network. The model predicts that the rate of aging, defined by the Gompertz coefficient, is proportional to the number of active interactions per gene and that stochastic heterogeneity is an important factor in shaping the dynamics of the aging process. Hence, the Gompertz parameter is a proxy of network robustness. Preliminary studies on how aging is influenced by power-law configuration, synthetic lethal interaction, and allelic interactions will be presented. A general framework to study network aging as a quantitative trait will be studied, and the implication on missing heritability will be investigated. Empirical results to support these theoretic studies will also be presented. Preprint for the basic model is available at http://arxiv.org/abs/1305.5784
Hong Qin
Spelman College
Biology
Molecular and Structural Biosciences
13
OSG-XSEDE
208
cms.org.northwestern
CMS Connect at Northwestern University
Mayda Velasco
Northwestern University
Physics
High Energy Physics
18
CMS Connect
706
FSU_Kolberg
Search for Higgs boson decays to long-lived scalar particles
Ted Kolberg
Florida State University
Physics
Physics
14
OSG Connect
42
UPRRP-MR
In this collaborative project between bioinformatics and physics we use molecular evolution simulations to evolve a population of proteins. We look for the emergence of mutational robustness of proteins in the population. This quantity measures how resistant they are to the deleterious effects of mutations. Previous results from Dr. Massey's group suggest that mutational robustness increases and eventually converges over time. This appears to be an emergent property of proteins. It has profound evolutionary implications.
The protein structures are obtained from the Protein Data Bank. Non-robust sequences are threaded onto the structure and are subjected to random mutations. The resulting sequences are selected for their free energy of folding. Once the sequences are generated the mutational robustness is calculated in parallel (through Condor).
Steven Massey
Universidad de Puerto Rico, Rio Piedras Campus (UPRRP)
Physics / Biology
Bioinformatics
30
OSG
805844088
UA_OIT
Our goal is to educate researchers on how to use OSG to perform their research. We have researchers working on medical technology, biology, chemistry, data science, machine learning, and artificial intelligence.
Donald Jay Cervino
University of Alabama
Office of Information Technology
Computer and Information Services
14
OSG Connect
703
GWU_OTSStaff
The Columbian College Office of Technology Services (OTS) is the primary technology services provider for the Columbian College of Arts and Sciences. OTS implements technology strategy, policies, and operational procedures in support of the College's instructional, research, and administrative functions. Serving a total user population of 9,000 constituents spread across five campuses, OTS strives to provide fast, reliable, and efficient service. https://ots.columbian.gwu.edu/
Janis Nicholas
George Washington University
Office of Technology Services
Computer and Information Sciences
14
OSG Connect
272
atlas.org.uci
ATLAS Connect team for University of California, Irvine
Robert William Gardner Jr
University of California, Irvine
Physics
High Energy Physics
16
ATLAS Connect
754032593
BNL_Venugopalan
We investigate the dynamics of strongly interacting field theories through a variety of numerical methods, ranging from classical lattice simulations to tensor network projects.
Raju Venugopalan
Brookhaven National Laboratory
Physics
Physics
151
PainDrugs
Virtual screening for novel anesthetic compounds.
Pei Tang
University of Pittsburgh
Anesthesiology
Medical Sciences
14
OSG Connect
543
SimCenter
Research Computing Facility providing HPC/HTC resources for local users
Anthony Skjellum
University of Tennessee at Chattanooga
Computer Science
Computer Science
14
OSG Connect
244
microphases
Periodic microphases universally emerge in systems for which short-range inter-particle attraction is frustrated by long-range repulsion. The morphological richness of these phases makes them desirable material targets, but our relatively coarse understanding of even simple models limits our grasp of their assembly. The OSG computing resources will enable us to explore more solutions of the equilibrium phase behavior of a family of similar microscopic microphase formers through specialized Monte Carlo simulations.
Patrick Charbonneau
Duke University
Chemistry
Chemistry
14
OSG Connect
371
IVSelection
We could like to preform instruments selection in the IV model by Machine Learning technique, and estimated the structure parameters by GMM method.
Hao Xu
University of California, Riverside
Econimics
Economics
14
OSG Connect
280
atlas.org.utdallas
ATLAS Connect Team for University of Texas - Dallas
Robert William Gardner Jr
University of Texas at Dallas
Physics
High Energy Physics
16
ATLAS Connect
839
UMiss_Stein
Numerical Relativity and Gravitational-wave physics
Leo Stein
University of Mississippi
Physics and Astronomy
Physics
14
OSG Connect
1486113095
Caltech_Vallisneri
The NANOGrav collaboration is a cross-university, cross-discipline collection of astrophysicists, data analysts, and engineers who are currently working to detect a gravitational wave background via Pulsar Timing Arrays (PTAs). Our group's current projects are related to cross-validation and posterior predictive checking methods for parameter estimation and detection analyses for Bayesian PTA studies. Another project is related to increasing computational efficiency of PTA analyses by developing likelihood reweighting methods for PTAs. More information on NANOGrav can be found here: http://nanograv.org/
Michele Vallisneri
California Institute of Technology
California Institute of Technology
Astronomy and Astrophysics
715
XSEDE_ECSS
Support for XSEDE users through ECSS
Robert Sinkovits
University of California, San Diego
San Diego Supercomputing Center
Computer Science
14
OSG Connect
48956063
UWMadison_Banks
Our project utilizes an fMRI regularization penalty to sparsify large-scale (up to 216 channels) MVAR models fitted to EEG brain data. Through sparsification of these models, we can do a better job of capturing brain connectivity with only a small amount of training data.
Matthew Banks
University of Wisconsin-Madison
Anesthesiology
Electrical, Electronic, and Communications Engineering
14
OSG Connect
534
AMNH
American Museum of Natural History
Michael Benedetto
American Museum of Natural History
N/A
Multi-Science Community
14
OSG Connect
854055598
USC_Rahbari
The present project aims at developing a multi-fidelity platform for uncertainty quantification of the air flow simulations over a common aerodynamic object. Thousands of low-fidelity, yet fast, simulations are required to construct the basis of this platform.
Iman Rahbari
University of Southern California
Center for Advanced Research Computing
Mechanical Engineering
14
OSG Connect
590554354
Gateway_DistribMedicalAI
Developing a job submission template for common medical AI imaging applications.
Hieu Nguyen
Rowan University
Mathematics
Medical Imaging
14
OSG Connect
1092373302
IIT_Kang
Create new statistical learning methodologies and machine learning algorithms
Lulu Kang
Illinois Institute of Technology
Applied Mathematics
Data Science
14
OSG Connect
466
Radlife
study of the real-time monitoring of space and earth weather, cosmic ray radiation and cancer formation, cosmic ray muon tomography, etc...
Xiaochun He
Georgia State University
Physics
Physics
14
OSG Connect
418
IITPROSPECT
Monte Carlo generation and data analysis for the PROSPECT experiment.
Bryce Littlejohn
Illinois Institute of Technology
Physics
High Energy Physics
14
OSG Connect
447909116
NichollsState_Whitaker
Use genetic and epigenetic approaches to answer ecological and evolutionary questions with a specific interest in applications to conservation and management of species
Justine Whitaker
Nicholls State University
Biological Sciences
Biological and Biomedical Sciences
14
OSG Connect
443
PopDy
Population dynamics across all species including human being. The life history, energy consumption, mortality pattern, and evolution paths and directions.
Shripad Tuljapurkar
Stanford University
Biology
Biological Sciences
14
OSG Connect
1702226924
SPRI_Smith
use high throughput computing to perform thousands of variations in virtual surgical decisions to assess optimal plans for patients
Colin Smith
Steadman Philippon Research Institute
Department of Biomedical Engineering
Bioengineering & Biomedical Engineering
14
OSG Connect
263
atlas.org.okstate
ATLAS Connect team for Oklahoma State University
Robert William Gardner Jr
Oklahoma State University
Physics
High Energy Physics
16
ATLAS Connect
630
Sandia_LandModel
Developing a "cheaper" surrogate land model.
Vishagan Ratnaswamy
Sandia National Laboratories
Earth Science
Earth and Ocean Sciences
14
OSG Connect
669
COVID19_UCSD_Hsiao
Develop AI algorithm to diagnose CT scans of pneumonia patients for COVID-19: https://www.kpbs.org/news/2020/apr/07/ucsd-using-ai-identify-pneumonia-coronavirus/
Albert Hsiao
University of California, San Diego
Radiology
Radiological Science
14
OSG Connect
487
Lariat
Project entry corresponding to Lariat VO.
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
140
gem5
The work is looking into microarchitectural details utilizing gem5 to do cycle-accurate simulation of an O3 processor. The work additionally uses McPAT and Hotspot to flush out the research framework.
Dean Tullsen
University of California, San Diego
Computer Science and Engineering
Multi-Science Community
14
OSG Connect
1380245457
NCSU_Staff
Continue my access to the OSPool after the OSG School to further support potential users and workflows for NC State University
Christopher Blanton
North Carolina State University
Research Facilitation Service
Other
791
UCSD_Wuerthwein_CMSUAF
Work submitted as part of the CMS analysis group at the physics department at UCSD
Frank Wuerthwein
University of California, San Diego
Physics Department
Physics
4
UCSD
966754372
UAB_ResearchComputing
Research Computing in IT at the University of Alabama - BirminghamResearch Computing in IT at the University of Alabama - Birmingham.
Ralph Zottola
The University of Alabama at Birmingham
Research Computing
Research Computing
14
OSG Connect
835
PennState_Hanna
Detection of gravitational waves from compact binary sources
Chad Hanna
Pennsylvania State University
Physics
Physics
14
OSG Connect
53
gridsgenomes
The use of methylation-specific restriction enzymes to preferentially cleave 5'-CCGG-3' sites in conjunction with Next Generation Sequencing platforms has formed the basis for the widely used Methyl-seq and HELP-tagging assays. The recent development of an R package using a Bayesian hierarchical model approach, msBayes, offered a statistically rigorous alternative to the basic tag-counting/geometric mapping previously used for these two techniques. Its dependence on the WinBUGS package however, severely limited its performance and usage by the community. We have re-implemented msBayes to make use of both OpenBUGS and OpenMP, and have integrated this new core module, msBayes2.0, into a web-based platform and subsequent deployment and processing on a diversity of computing platforms.
David Rhee
Albert Einstein College of Medicine
Genetics
Biological Sciences
30
OSG
101
compcomb
Computational Combinatorics uses significant computational resources to solve problems in combinatorics, graph theory, and discrete mathematics.
Derrick Stolee
Iowa State University
Mathematics
Mathematical Sciences
67
HCC
1255246248
UALR_ITS
Accounts for ITS staff members at the University of Arkansas, Little Rock
Timothy Stoddard
University of Arkansas at Little Rock
IT Services
Research Computing
14
OSG Connect
136
cms-org-nd
CMS Connect at Notre Dame
Kevin Lannon
University of Notre Dame
High Energy Physics
High Energy Physics
18
CMS Connect
2025707023
MTU_Sha
My methodological research projects focus on the development of novel statistical methods and efficient bioinformatical tools to address problems from genome-wide association studies and phenome-wide association studies.
Qiuying Sha
Michigan Technological University
Department of Mathematical Sciences
Mathematics
14
OSG Connect
850
NSDF
Project for the National Science Data Fabric's investigations of the Open Science Data Federation, and other data movement within the OSG Consortium.
Frank Wuerthwein
University of California, San Diego
San Diego Supercomputing Center
Computer Sciences
14
OSG Connect
965071200
Seattle_Herman
Teaching a distributed systems course. Assignments will be at-scale applications including a parallel video rendering pipeline, a genome analysis application, and a text analysis workflow.
Nate Kremer-Herman
Seattle University
Computer Science
Computer and Information Sciences
150
MiniWorkshopUC15
Open Science Grid Mini-Workshop at University of Chicago on April 9th 2015
Robert William Gardner Jr
University of Chicago
Computation Institute
Computer and Information Science and Engineering
14
OSG Connect
565
WayneStateU_Staff
Staff at Wayne State University's HPC Services
Michael Thompson
Wayne State University
High Performance Computing Services
Multi-Science Community
14
OSG Connect
419
SpatialModeling
Developing software applications for probabilistic graph models, predominantly for spatially explicit modeling.
Brook Milligan
New Mexico State University
Biology
Bioinformatics
14
OSG Connect
505
cyverse
CyVerse is a cyberinfrastructure project (formerly iPlant Collaborative). This project will be an umbrella for initial testing of OSG integration, with the hope that eventually we will instead ask users for their own projects to submit with jobs.
Nirav Merchant
University of Arizona
Biology
Biological Sciences
14
OSG Connect
86
Orbiter
The goal of this project is to create farmed data in the form of classifications of discrete structures from mathematics. This data farm can be used to support discovery of new objects and constructions.
Anton Betten
Colorado State University
Department of Mathematics
Mathematical Sciences
14
OSG Connect
83
UCSDPhysBio
Biological Physics from UCSD supported users
Frank Wuerthwein
University of California, San Diego
Physics
Biophysics
4
UCSD
121
megaprobe
high performance sequence analysis
Humberto Ortiz-Zuazaga
University of Puerto Rico
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
1711642752
UTSouthwestern_Lin
Access the molecular organization and fluctuations of the condensate with atomistic simulations
Milo Lin
University of Texas Southwestern Medical Center
Department of Biophysics
Biological and Biomedical Sciences
14
OSG Connect
565863889
UWMadison_Solis-Lemus
Using machine learning methods to identify sounds from audio recordings in multiple regions of the world through time.
Claudia Solis-Lemus
University of Wisconsin-Madison
Plant Pathology
Biological Sciences
63
atlas.org.uchicago
Tier3 computing for the UChicago ATLAS group via the ATLAS Connect service
Robert William Gardner Jr
University of Chicago
High Energy Physics
High Energy Physics
16
ATLAS Connect
453
cms.org.cern
CMS Connect group for CERN
Achille Petrilli
CERN
Physics
Particle Physics
18
CMS Connect
56
CometCloud
CometCloud is an autonomic framework for enabling real-world applications on dynamically federated, hybrid infrastructure integrating (public & private) clouds, data-centers and Grids. Specifically, CometCloud provides abstractions and mechanisms to support a range of programming paradigms and real-world applications on such an infrastructure. Furthermore, it enables policy-based autonomic cloud-bridging and cloud-bursting. Autonomic cloud-bridging enables on-the-fly integration of local computational environments (data-centers, grids) and public cloud services (such as Amazon EC2), and autonomic cloud-bursting enables dynamic application scale-out to address dynamic workloads, spikes in demands, and other extreme requirements. Currently, we support various applications as part of our collaborations in multiple domains such as medical diagnostics, material sciences, biology, and engineering.
Javier Diaz-Montes
Rutgers, The State University of New Jersey
Electrical and Computer Engineering
Computer and Information Science and Engineering
30
OSG
187
NeoflAnnot
Generation of a transcriptome for the copepod Neocalanus flamingeri in the gulf of Alaska.
Petra Lenz
University of Hawaii at Manoa
Pacific Biosciences Research Center
Biological Sciences
14
OSG Connect
475
MOmega
Looking at agreement of African triage data using Meier's Omega
Maxene Meier
University of Colorado
School of Public Health
Statistics
14
OSG Connect
166
EvolSims
Evolutionary simulation tracking gene frequencies under a variety of environmental conditions.
Oana Carja
University of Pennsylvania
Biology
Biological Sciences
14
OSG Connect
1778701075
TG-MCH210037
Engineering the electro-mechanical properties of Twisted Bilayer Graphene with strained capping layers
Hesam Askari
University of Rochester
Mechanical Engineering
Mechanical Engineering
14
OSG Connect
802
ASU_Ozkan
In this research, we are trying to study and calculate the binding free energy of protein complexes with large peptides. The strategy is to apply constant velocity pulling on peptides based on NAMD simulations and statistically calculate the binding free energy by applying Jarzynskis equality.
Banu Ozkan
Arizona State University
Physics
Physics
14
OSG Connect
1617569803
UF_Strother
The Strother Lab focuses on questions at the interface between physiology and physics. Our lab is especially interested in understanding processes at multiple levels of organization, from the properties of individual cells up to the responses of the whole animal. Current projects in the lab examine a range of topics, including the effects of stress on animal behavior, nervous control of the cardiovascular system, and sensory physiology. See also www.strotherlab.org.
James Strother
University of Florida
Whitney Laboratory for Marine Bioscience
Neuroscience, biomechanics, microscopy
820
NMSU_SpinQuest
SpinQuest will investigate whether the sea quarks are orbiting around the center of the nucleon by exploring the nucleon in a particular way
Stephen Pate
New Mexico State University
Physics
Physics
14
OSG Connect
476
sugwg
Gravitational-wave astronomy and astrophysics.
Duncan Brown
Syracuse University
Physics
Astrophysics
14
OSG Connect
761
IAState_ITStaff
Test accounts for Research IT staff at Iowa State
James Coyle
Iowa State University
High Performance Computing
Computer Sciences
14
OSG Connect
92
atlas.org.indiana
Indiana University Tier 3 ATLAS group.
Frederick Luehring
Indiana University
Physics
High Energy Physics
16
ATLAS Connect
1989474490
TAMUCT_Thron
Large-scale agent-based simulations; stochastic optimization; training of neural networks
Christopher Thron
Texas A&M University-Central Texas
Department of Science and Mathematics
Mathematics and Statistics
744
MIT_Choi
Simulating dynamics of strongly interacting quantum many-body systems
Soonwon Choi
Massachusetts Institute of Technology
Center for Theoretical Physics
Physics
14
OSG Connect
387784568
IIT_Minh
Computational scientists who focus on chemical biology, the interactions between small molecules and biological macromolecules. We develop and apply new methods that may be helpful for structure-based drug design.
David Minh
Illinois Institute of Technology
Chemistry
Biological and Biomedical Sciences
701
TG-CHE200063
Unraveling Crystallization and Phase Transition Processes through Topology, Rare-event Simulation, and Machine Learning
Jerome Delhommelle
University of North Dakota
Chemistry
Chemistry
13
OSG-XSEDE
229
cms.org.tamu
CMS Connect at Texas A&M University
Alexei Safonov
Texas A&M University
Physics
High Energy Physics
18
CMS Connect
775
GATech_PACE
Partnership for an Advanced Computing Environment (PACE) provides faculty participants a sustainable leading-edge high performance computing (HPC) infrastructure with technical support services.
Ruben Lara
Georgia Institute of Technology
PACE
Computer Science
14
OSG Connect
417
SSGAforCSP
This project will use the OSG to demonstrate the feasibility of using a new steady state genetic algorithm (SSGA), recently introduced by the MGAC collaboration, to predict the crystal structures of molecules of pharmaceutical interest. The OSG resources are ideal for this project because the SSGA requires a large number of independent energy calculations of candidate structures. These calculations for simple molecules will use the DFT approach, using software already available in the OSG.
Julio Facelli
University of Utah
Biomedical Informatics
Bioinformatics
14
OSG Connect
376
TG-AST160046
Our ultimate goal with this proposal is to understand how magnetic dynamos work on stars other than the Sun. To do
the science we propose which is to measure the typical starspot lifetime as a function of rotation rate and stellar mass and derive the starspot number and the spatial starspot distribution for stars other than the Sun, we must apply our light curve model
ing program to the full duration (4 years) of publicly available short cadence Kepler time series photometry of as many of our targets as possible. We must run the code many times per target in a Monte Carlo fashion in order to explore the full parameter s
pace of potential solutions. We must also do trials with different numbers of starspots in order to determine the optimal number of spots necessary to fit the light curves. For this initial research allocation, we proposal to use the Open Science Grid to
do a series of runs for 5 high priority targets: HAT-P-11, Kepler-17, Kepler-63, KOI-340, and KOI-1786, using our STSP code designed specifically for high throughput computing. The core code for the work has already been completed. Now, we need to run i
t many times in many different configurations in order extract the scientific results. This mode of operating is well suited to training the young students and scientists that will do this work.
Leslie Hebb
Hobart and William Smith Colleges
Physics
Physics
13
OSG-XSEDE
712
Michigan_Riles
Continuous gravitational waves
Keith Riles
University of Michigan
Physics
Gravitational Physics
14
OSG Connect
1775226506
MSU_RCI
Montana State University - RCI staff
Alex Salois
Montana State University
Research Cyberinfrastructure
Computer Science
1319306625
UCSD_Pa
Big data approaches to investigating modifiable risk factors and lifestyle-based interventions in Alzheimer's disease
Judy Pa
University of California, San Diego
School of Medicine, Alzheimer’s Disease Cooperative Study (ADCS)
Biological Sciences
14
OSG Connect
711
SWOSU_SOCCER
Helping SWOSU students and faculty start running jobs on HTC resources in support of training and growing an HTC capable resource.
Jeremy Evert
Southwest Oklahoma State University
Computer Science
Computer and Information Sciences
14
OSG Connect
1240428427
Rochester_Askari
Engineering the electro-mechanical properties of Twisted Bilayer Graphene with strained capping layers
Hesam Askari
University of Rochester
Mechanical Engineering
Mechanical Engineering
14
OSG Connect
89
OSGOpsTrain
Training project for OSG Operations staff.
Rob Quick
Open Science Grid
GOC
Community Grid
14
OSG Connect
67
HTCC
This project will be used for the OSG AHM HTC Challenge. It may also be the home of future challenges.
Rob Quick
Indiana University
Research Technologies
Community Grid
30
OSG
258
atlas.org.louisville
University of Louisville
Robert William Gardner Jr
University of Louisville
Physics
High Energy Physics
16
ATLAS Connect
752
UCSD_Hsiao
Develop AI algorithm to diagnose CT scans of pneumonia patients: https://www.kpbs.org/news/2020/apr/07/ucsd-using-ai-identify-pneumonia-coronavirus/
Albert Hsiao
University of California, San Diego
Radiology
Radiological Science
14
OSG Connect
577
UCI_Jeliazkov
Ivan Jeliazkov
University of California, Irvine
Economics
Economics
14
OSG Connect
795
MIT_Hill
This is for NSF-NASA efforts to create very large realistic models of the Earths oceans ( https://data.nas.nasa.gov/ecco/ ). Some of our largest modeling efforts produce multi-petabyte solutions and we are experimenting with sharing via the NSF Open Storage Network to provide broad open access to datasets that are increasingly widely used. We are interested in undertaking high-throughput analysis to identify ocean vorticity feature statistics in different model solutions to better understand air-sea feedbacks that are significant for better modeling climate processes. We are also interested in creating scripts that we can share widely with downstream users throughout the US and globally. We will be using the OSN object store accessed through the Python s3fs and xarray tools. These allow high concurrency access for reading different objects within the project OSN S3 buckets.
Chris Hill
Massachusetts Institute of Technology
Earth, Atmospheric and Planetary Sciences
Earth and Ocean Sciences
14
OSG Connect
31
PlantBio
Investigation of plant-pathogen interactions using genome-wide association mapping.
Joy Bergleson
University of Chicago
Ecology and Evolution
Plant Biology
14
OSG Connect
124762769
Creighton_Kokensparger
Digitally analyzing handwritten burial permit records from an historic cemetery.
Brian Kokensparger
Creighton University
Computer Science, Design & Journalism Department
Computer and Information Services
14
OSG Connect
642
PercARsolar
Project entails the participation of a number of students in a graduate level class in running a code that simulates the evolution of solar active regions as a percolation phenomenon. A number of students will continue the research as part of their Master's thesis at Chicago State University. Computationally, the project builds upon work done previously by Seiden and Wentzel, by adding a new algorithm in tracking the polarity of the magnetic field structures on the solar photosphere. Requirements for the project is python version 3+. Typical single core walltime of each job is 1 hour for a modest resolution of a 2D grid. Upper limit of walltime is about 3 hours for the highest resolution consistent with the limitations of the algorithm.The project seeks to determine the steady state of the solar cycle by varying the emergence and diffusion probability parameters of magnetic flux tubes. The percolation engine is inherently chaotic and finely tuned values for these parameters are sought in a sweep of the probability space through a large volume of jobs.
Pascal Paschos
Chicago State University
Astronomy
Astronomy
14
OSG Connect
814
Michigan_Knowles
Population genetics and demography
L. Lacey Knowles
University of Michigan
Ecology and Evolutionary Biology
Biological Sciences
14
OSG Connect
618
SCEPCAL_Tully
Segmented Crystal Electromagnetic Precision Calorimeter (for CEPC: Circular Electron Positron Collider and possibly other future collider experiments, e.g. the FCC)
Christopher Tully
Princeton University
Physics
Physics
14
OSG Connect
1978977404
Columbia_Alquraishi
Building a model of protein sequence to structure relationships and using it to predict the DNA binding motifs of transcription factors based on their structure.
Mohammed Alquraishi
Columbia University
Department of Systems Biology
Biological Sciences
14
OSG Connect
5
DetectorDesign
Investigate how different simulated SPECT system geometries can affect reconstructed images.
John Strologas
University of New Mexico
Physics and Astronomy
Medical Sciences
30
OSG
686
AMNH.astro
Department of Astronomy at the American Museum of Natural History
Mordecai-Mark Mac Low
American Museum of Natural History
Astronomy
Astronomy
14
OSG Connect
2130774909
UWMadison_Curtin
https://arc.psych.wisc.edu/
John Curtin
University of Wisconsin-Madison
Psychology
Social, Behavioral & Economic Sciences
231
cms.org.virginia
CMS Connect at University of Virginia
Brad Cox
University of Virginia
Physics
High Energy Physics
18
CMS Connect
143
cms.org.fnal
CMS Connect group for FNAL
Lothar Bauerdick
Fermilab
Physics
High Energy Physics
18
CMS Connect
1460430150
OHSU_Katamreddy
Cardiovascular disease occurs due to environmental factors like diet, exercise but also due to genetic predisposition. I want to work on finding genetic pathways that underlie the genesis cardiovascular disease. Please find link to my previous work on cardiovascular disease and medicine. Adarsh Katamreddy - Google Scholar
Adarsh Katamreddy
Oregon Health & Science University
Cardiovascular Medicine
Medical Sciences
14
OSG Connect
485
darkside
Project entry for the Darkside VO. http://darkside.lngs.infn.it/
Joe Boyd
Darkside
N/A
High Energy Physics
103
Darkside
1777853614
FIU_DCunha
To implement a reconfigurable compute environment, RAPTOR proposes to adopt the Chameleon Cloud Infrastructure for on-demand resource allocation, and the Open Science Grid (OSG)
Cassian D’Cunha
Florida International University
Department of Information Technology
NSF RAPTOR Project / Computer and Information Systems
14
OSG Connect
1033099510
TG-TRA120012
UCLA Campus champion allocation
Tajendra Vir Singh
University of California, Los Angeles
OARK
Computer Science
14
OSG Connect
1842147504
CedarsSinai_Meyer
The Platform for Single-Cell Science is a tool for improving both the reproducibility and accessibility of analytical pipelines developed for single-cell multiomics. Researchers will be able to upload their data, create an analysis pipeline using our javascript designer, and link their results to a publication. The raw data, analysis, and results will be made available for interactive exploration or download when users are ready to publish. We are hoping to understand if there is a way we can use OSG by sending jobs that are prepared on our website hosted on AWS to the OSG for execution.
Jesse Meyer
Cedars-Sinai Medical Center
Computational Biomedicine
Biological and Biomedical Sciences
159
SDEalgorithms
The goal of the project is to develop fast, accurate algorithms for simulation and inference of stochastic differential equations (SDE). Many SDE models of interest in science feature drift and diffusion coefficients with superlinear growth, which causes convergence and stability problems for many time integrators. We seek improved methods that can overcome these problems, with a focus on correctly computing moments and densities of the solution.
Harish S. Bhat
University of California, Merced
Applied Mathematics
Mathematical Sciences
14
OSG Connect
1970554877
USC_CARC
USC Center for Advanced Research Computing Facilitators
BD Kim
University of Southern California
Center for Advanced Research Computing
Computer Science
14
OSG Connect
507
polymer
Investigate the thermal conductivity of polymer and polymer
composites using MD simulation
rajmohan muthaiah
University of Oklahoma
Mechanical Engineering
Materials Science
14
OSG Connect
123
TG-OCE140013
Methods that integrate population sampling from multiple taxa into a single analysis are a much needed addition to the comparative phylogeographic toolkit. Here we present a statistical framework for multi-species analysis based on hierarchical approximate Bayesian computation (hABC) for inferring community dynamics and concerted demographic response. Detecting community response to climate change is an important issue with regards to how species have and will react to past and future events. Furthermore, whether species responded individualistically or in concert is at the center of related questions about the abiotic and biotic determinants of community assembly. This method combines multi-taxon genetic datasets into a single analysis to determine the proportion of a contemporary community that historically expanded in a temporally clustered pulse as well as when the pulse occurred. We will apply this method to 59 species in the Hawaiian Archipelago in order to examine community response of coral reef taxa to sea-level change in Hawaii. The method can accommodate dataset heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and utilizes borrowing strength from the simultaneous analysis of multiple species. This hABC framework used in a multi-taxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently, and can be used with a wide variety of comparative phylogeographic datasets as biota-wide DNA barcoding data sets accumulate.
Yvonne Chan
University of Hawaii at Manoa
Hawaii Institute of Marine Biology
Ocean Sciences
13
OSG-XSEDE
131
Genie
Generates Events for Neutrino Interaction Experiments(GENIE) is a universal object-oriented neutrino MC generator supported and developed by an international collaboration of scientists whose expertise covers a very broad range of neutrino physics aspects, both phenomenological and experimental. GENIE is currently being used by T2K, NOvA, MINERvA, MicroBooNE, ArgoNEUT, LAGUNA-LBNO, LBNE, INO, IceCUBE, NESSiE and others.
Gabriel Nathan Perdue
Fermilab
Scientific Computing Simulation
High Energy Physics
9
Fermilab
162
TG-MCB140268
The genome of many viruses is represented by a long single-stranded ribonucleic acid (RNA) molecule that appears to fold into a highly compact organized structure inside the viral shell. Such structure contains a variety of topological motifs, such as hairpins, bulges, multi-loops, and notably RNA pseudoknots. RNA pseudoknots play an important role also in natural RNAs for structural, regulatory and catalytic functions in various biological processes. In particular, it has been recently recognized an interesting interplay between the shape, structure and assembly of icosahedral viral capsids, and the compact RNA packaging topology. The topology of RNA pseudoknots can be effectively studied by using Random Matrix Theory (RMT), by exploiting a correspondence between a graphical representation of RNA structures with pseudoknots and Feynman diagrams of a particular field theory of large random matrices. The theoretical framework of RMT provides a natural analytic tool for the prediction and classification of pseudoknots, since all Feynman diagrams can be organized in a mathematical series, called topological expansion. The PI is interested in studying numerically some recent matrix models based on RMT to describe the structure of viral RNA encapsidated in a viral icosahedral shell. The PI has long experience in the application of RMT to the study of RNA pseudoknots with RMT, as well as on the simulation of the geometry and shapes of icosahedral shells.
The simulations the PI intends to perform on XSEDE are Monte Carlo runs of large stochastic matrices, since the matrix model is naturally formulated as zero-dimensional SU(N) field theory of Hermitian matrices. The number of matrices L is equal to number of nucleotides of the RNA molecules, which in viral RNAs can be of the order of L~10^3. Past preliminary studies showed that the size N of the matrices should be sufficiently large to appreciate topological corrections of the order 1/N^2 and 1/N^4 (at least), which implies the simulation of Hermitian random matrices of order N~24 or N~32. Since the number of degrees of freedom for each matrix is N^2~1024, the configuration space has L*N^2~ 10^6 degrees of freedom. While matrix multiplication can benefit of parallel computing capabilities, the need of performing Monte Carlo simulations orients the PI to request High Throughput Computing resources for this initial XSEDE Startup application. Such initial experience will provide the PI a baseline to evaluate the possibility to steer future versions of the code towards HPC capabilities, including GPU or CPU-GPU clusters. Current local computational capabilities are sufficient for developing the codes and running toy-model simulations (N~4), but do not satisfy the PI’s needs for research purposes of large realistic systems. Therefore, XSEDE startup resources are requested to test larger systems, optimize the code and explore code’s scalability, as well as familiarize with the XSEDE platform.
(1 row)
Graziano Vernizzi
Siena College
Physics and Astronomy
Molecular and Structural Biosciences
13
OSG-XSEDE
161
GenomicIntegration
Integration of publicly available large-scale genomic data.
Casey Greene
Dartmouth College
Genetics
Bioinformatics
14
OSG Connect
542618163
SLAC_Nelson
The Light Dark Matter eXperiment (LDMX) is a search for sub-GeV (lighter than the proton) thermal dark matter particles
Timothy Nelson
SLAC National Accelerator Laboratory
Fundamental Physics Directorate, HPS Department
Physics
14
OSG Connect
176
EvolvingAI
Modern day software and robotics are notorious for lacking robustness and adaptability, often breaking down when encountering unexpected situations. Natural animals, on the other hand, are well known for their robustness and their ability to adapt to new environments. The Evolving Artificial Intelligence project aims to study how the robustness and adaptability of natural animals evolved, both to learn more about natural evolution, and to increase the robustness and adaptability of modern software and robotics systems.
Jeff Clune
University of Wyoming
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
893636859
TG-PHY210092
Finite-size corrections in spin glasses and combinatorial optimization
Stefan Boettcher
Emory University
Department of Physics
Condensed Matter Physics
13
OSG-XSEDE
463
HASHA
Program uses NCBI’s Entrez.efetch on the nucleotide database to take in large number of sequences and searches the sequences for palindromes ranging in size from 4 to 20 and appends the results to a list. The program then takes each palindrome and checks for its occurrence on the 11 genes of the influenza A virus’s and outputs every match of the palindrome with relevant sequence Information.
Brian Cheda
Arcadia University
Biology
Bioinformatics
14
OSG Connect
16
spt.all
The South Pole Telescope (or SPT) is a new telescope deployed at the South Pole that is designed to study the Cosmic Microwave background. Constructed between November 2006 and February 2007, the SPT is the largest telescope ever deployed at the South Pole. This telescope provides astronomers a powerful new tool to explore dark energy, the mysterious phenomena that may be causing the universe to accelerate.
John Carlstrom
University of Chicago
Kavil Institute for Cosmological Physics
Astrophysics
14
OSG Connect
1942455935
OSG_SoftwareInventory
OSG Security Team collaboration group currently working on building a worker node scanning tool. They are using OSG Connect for testing this tool. This group of researchers will likely evolve over time, as will their projects and collaborations. As of October 2023, Josh Drake is a point of contact.
Josh Drake
OSG
Computing Sector (OSG Security Team)
Computer and Information Science and Engineering
30
OSG
1466529550
LSU_Cox
Using machine learning techniques that discover solutions with anatomically and temporally structured sparsity, we aim to test representational predictions from cognitive psychology using whole-brain neuroimaging datasets.
Christopher Cox
Louisiana State University
Department of Psychology
Behavioral Science
2126152924
TG-ASC180023
Campus Champion Guided Discovery of XSEDE Resources for Region 7 at the Roux Institute at Northeastern University
Scott Valcourt
Northeastern University
Roux Institute
Applied Computer Science
14
OSG Connect
405
GLUEX
GlueX project
Kurt Strosahl
Jefferson Lab
Physics
Nuclear Physics
99
JLab
225
cms.org.rockefeller
CMS Connect at Rockefeller University
Dino Goulianos
Rockefeller University
Physics
High Energy Physics
18
CMS Connect
765
UPenn_Ramdas
Identifying causal Mendelian genes for neurodevelopmental disorders using singletons
Shweta Ramdas
University of Pennsylvania
Genetics
Health
14
OSG Connect
579
UCSD_YZYou
Numerical verification of the entanglement feature (EF) approach to modeling the second Renyi entropy growth of a random circuit. We will compare the exact calculation to the calculation using the EF Hamiltonian, derived separately using analytical techniques.
Yi-Zhuang You
University of California, San Diego
Physics
Physics
14
OSG Connect
743
COVID19_JHU_Howard
One of the biggest challenges facing the US healthcare system in caring for patients with COVID-19 is the limited number of ICU beds and ventilators available, in addition to concerns regarding staffing levels. Hospital cooperation can allow for patient transfers increasing the efficiency of the overall system and the number of patients who can receive treatment. We use data from COVID-19 in Maryland to formulate a mathematical model which can determine which hospitals are the best candidates for the patient transfer, accounting for the current and expected resource usage in all hospitals. The advantages of the mathematical model are demonstrated with simulation of the spread of COVID-19 in Maryland.
James P. Howard, II
Johns Hopkins University
Mathematics
Mathematical Sciences
14
OSG Connect
403
MaizeAminoAcids
The amino acid content in maize kernels is critically important for human and animal nutrition. However, the genetic basis underpinning amino acids is not fully understood. We are performing Genome Wide Association Studies and Genomic prediction in a panel of several thousand maize plants genotyped at tens of millions of loci to finely dissect amino acid traits in maize.
Timothy M Beissinger
University of Missouri
Divison of Plant Sciences
Evolutionary Sciences
14
OSG Connect
1470146509
Harvard_Fox
Computational analysis of functional neuroimaging data to identify brain circuits and potential therapeutic stimulation targets.
Michael Fox
Harvard University
Center for Brain Circuit Therapeutics / Neurology
Biological and Biomedical Sciences
14
OSG Connect
65
KnowledgeLab
Knowledge Lab / CI
James Evans
University of Chicago
Computation Institute
Other
14
OSG Connect
355
DOSAR
Distributed Organization for Scientific Academic Research. International outreach projects sponsored by the DOSAR Virtual Organization. Students that would like to maintain accounts on OSG.
Rob Quick
DOSAR
HEP
Education
30
OSG
551
TG-TRA140036
Campus Champions Renewal
David Toth
Centre College
Computer Science
Training
13
OSG-XSEDE
848
GATech_Sholl
Atomically-detailed simulation methods (e.g. Molecular Dynamics, Monte Carlo and quantum chemistry methods) are used to develop models of molecular separations based on adsorption in structured nanoporous materials. These materials include zeolites, metal-organic framework materials, activated carbons and polymers. A long-term goal is the discovery of new adsorbent materials for a diverse range of chemical separations, a problem for which a very large search space exists.
David Sholl
Georgia Institute of Technology
Chemical & Biomolecular Engineering
Chemistry
14
OSG Connect
48
TG-STA110014S
Staff Account for Training
Nancy Wilkins-Diehr
University of California, San Diego
San Diego Supercomputer Center
Training
13
OSG-XSEDE
553220193
FNAL_Hoeche
Sherpa is a Monte Carlo event generator for the Simulation of High-Energy Reactions of PArticles in lepton-lepton, lepton-photon, photon-photon, lepton-hadron and hadron-hadron collisions. Simulation programs - also dubbed event generators - are indispensable computational tools for particle physics phenomenology and are the interface between theory and experiment.
Stefan Hoeche
Fermilab
Fermilab Theory Division
Physics
14
OSG Connect
171
oclab
Immunology at OConner's lab
Dave OConnor
University of Wisconsin-Madison
School of Medical and Public Health
Medical Sciences
14
OSG Connect
696
Columbia_Eaton
Computation for Plant Phylogenomics
Deren Eaton
Columbia University
Ecology, Evolution, and Environmental Biology
Biological Sciences
14
OSG Connect
640
GWU_TikidjiHamburyan
We are interested in mechanisms of establishing connectivity in the brain during the critical pre- and postnatal periods. The main focus of this project is on non-linear dynamics in growing networks.
Ruben Tikidji-Hamburyan
George Washington University
School of Medicine and Health Sciences
Biological Sciences
14
OSG Connect
41
TG-ATM130009
The aim of this project is to create a global map that describes the functional distributions which characterize the spectraof precipitating auroral particles. Such a map would not only aid in efforts to model the ionosphere and the geospatial environment, but would also aid in the understanding of the magnetospheric source regions of these particles. The construction of this map will utilize programs that perform automated, nonlinear least squares fits of Maxwellian and Lorentzian distributions to data from the Defense Meteorological Satellite Program (DMSP) suite of spacecraft. These programs have been developed in C under the Fedora Coredistribution and are statically linked against the HDF4 and GNU Scientific libraries. Initial testing on an AMD Athlon II X4 645quad core processor has shown that the serial execution of four separate instances of the Maxwellian automated fitting program produces fits at an average rate of 1500 spectra per hour per core, while the Lorentzian program, when executed in the same fashion, will produce fits at an average rate of 500 spectra per hour per core. The 20-year catalog of data which we will use to populate this map contains roughly 200 million spectra. With these average rates, it would take our 16-core cluster approximately 8300 hours to fit Maxwellian distributions and 25,000 hours to fit Lorentzian distributions to the entire catalog. Given this amount of processing time and the serial nature of our programs, we wish to explore the feasability of using your HTC resources to complete this project.
Phillip Anderson
University of Texas at Dallas
Physics
Atmospheric Sciences
13
OSG-XSEDE
721
MSU_Colbry
SEE-Insight: Scientific Image Understanding algorithm discovery using Simple Evolutionary Exploration
Dirk Colbry
Michigan State University
Computational Mathematics, Science and Engineering
Computer Science
14
OSG Connect
1820610269
UWMadison_Negrut
Chrono is a physics-based modelling and simulation infrastructure based on a platform-independent open-source design implemented in C++. Chrono is developed by the Negrut group; the goal is to make it available on the OSPool.
Dan Negrut
University of Wisconsin-Madison
Mechanical Engineering
Engineering
14
OSG Connect
382
CombinedPS
Design and control of exoskeletons (and prostheses) thus far has been primarily carried out following heuristic methods and exhaustive experimental (design and test) procedures. This approach significantly slows down design iterations and increases project costs. A predictive simulation framework for combined human and device dynamics is a valuable tool that can significantly accelerate optimal device and controller design.
We are building predictive models of combined muscuoloskeletal and exoskeleton dynamics for walking, where design parameters for the exoskeleton (such as actuation torque profiles) and various objective functions (such as metabolic cost) can be optimized simultaneously.
Ozkan Celik
Colorado School of Mines
Mechanical Engineering
Biological and Critical Systems
14
OSG Connect
649
SOLID
Jefferson Lab's SOLID experiment
Thomas Britton
Jefferson Lab
Physics
Nuclear Physics
99
JLab
266
atlas.org.pitt
ATLAS Connect team for University of Pittsburgh
Robert William Gardner Jr
University of Pittsburgh
Physics
High Energy Physics
16
ATLAS Connect
813
SDSU_Huangfu
Artificial intelligence and information sciences studies.
Luwen (Vivian) Huangfu
San Diego State University
Department of Management Information Systems
Computer and information services
14
OSG Connect
521
TG-CIE170062
This course will provide an overview of techniques in cluster computing, High Throughput Computing and High Performance computing. Students will start from the very basics of constructing a small two node cluster from first principles. Using this small cluster, students will learn a variety of topics about cluster configuration and management, files systems and how they affect workflows, constructing workflows, running applications locally and how to scale applications to larger systems. Initially the students will do most of their work on their two node clusters. We will then scale the workflows and run them using the University of Colorado High Energy Physics cluster; an OSG opportunistic resource provider (UColorado_HEP) and finally I would like to give the students the experience if running on very large systems. I do not envision the students needing high priority nor consuming large amounts of resources. I am much more interested in being able to provide the experience of "what is possible". The class will consist of between 30 and 40 students. Funding for this class comes from the United States State Department through the Fulbright Scholar Program.
Douglas Johnson
University of Colorado Boulder
Physics
Computer and Information Science and Engineering
13
OSG-XSEDE
426
asurcosg
Testing OSG integration with ASU HPC
Johnathan Lee
Arizona State University
Research Computing
Computer and Information Science and Engineering
14
OSG Connect
298
SourceCoding
Lossy compression is one of the classic problems in communication systems. The goal is to compress a given digital sequence so that it can be reconstructed up to a specific distortion (Shannon bound).
David Mitchell
New Mexico State University
Electrical Engineering
Engineering
14
OSG Connect
661
UCDenver_Farguell
Wildland Fire Modeling
Angel Farguell
University of Colorado Denver
Mathematical and Statistical Sciences
Atmospheric Science and Meteorology
14
OSG Connect
735
RIT_KGCEval
TBD
Carlos R. Rivero Osuna
Rochester Institute of Technology
Computing and Information Sciences
Computer Science
14
OSG Connect
1335741304
NJIT_Nadim
Work is concerned with uncovering the principles of underlying neural circuit function.
Farzan Nadim
New Jersey Institute of Technology
Biological Sciences
Biological and Biomedical Sciences
14
OSG Connect
310
TG-PHY150040
IceCube is a neutrino detector built at the South Pole by instrumenting about a cubic kilometer of ice with 5160 light sensors. IceCube is taking data since 2006, and it is envisioned to continuing doing so for the next 20 years. One of the primary goals for IceCube is to elucidate the mechanisms for production of high-energy cosmic rays by detecting high-energy neutrinos from astrophysical sources. The excellent performance of IceCube plus the advances in understanding fundamental detector characteristics such as the ice properties have allowed to expand its scientific reach towards measurements and searches that require much higher precision and control of systematic error sources. Examples of these are the measurement of neutrino oscillations in a previously unexplored energy range from 10 to 60 GeV. The simulations proposed in this request will enable carrying out neutrino physics precision analysis which require of a very good understanding of possible sources of systematic errors. Examples of these are Tau neutrino appearance and Muon neutrino disappearance precision measurements as well as searches for low energy sterile neutrinos.
Francis Halzen
University of Wisconsin-Madison
Physics
Physics and astronomy
13
OSG-XSEDE
331
TG-TRA140043
Campus Champion allocation
Igor Yakushin
Pennsylvania State University
Institute for CyberScience
Computer and Information Science and Engineering
13
OSG-XSEDE
214
cms.org.jhu
CMS Connect at Johns Hopkins University
Morris Swartz
Johns Hopkins University
Physics
High Energy Physics
18
CMS Connect
789
Michigan_Jadidi
Cave mapping with underwater robots using invariant common filter method.
Maani Ghaffari Jadidi
University of Michigan
Naval Architecture and Marine Engineering
Robotics
14
OSG Connect
246
atlas.org.albany
ATLAS Connect team for SUNY Albany
Robert William Gardner Jr
State University of New York at Albany
Physics
High Energy Physics
16
ATLAS Connect
662839851
TG-PHY210094
Magnetic and toopological properties of line defects in multiband superconductors. use Bogoliubov-de Gennes equations
Peter Hirschfeld
University of Florida
Physics dept.
Physics
14
OSG Connect
646
TG-TRA130003
Campus Champion Renew for Tufts University
Shawn Doughty
Tufts University
Research and Geospatial Technology Services
Training
13
OSG-XSEDE
689
LoyolaChicago_Li
quantum chemical simulations
Pengfei Li
Loyola University Chicago
Chemistry
Chemistry
14
OSG Connect
720
BNL_Schenke
High energy nuclear collision simulations for RHIC, LHC, and EIC
Bjoern Schenke
Brookhaven National Laboratory
Physics
Physics
14
OSG Connect
133
MS-EinDRC
For modeling and other computational projects of the Mt. Sinai-Einstein DRC and affiliates, primarily structurally related protein Modeling and Docking.
Jacob Pessin
Albert Einstein College of Medicine
Endocrinology
Medical Sciences
14
OSG Connect
2071458430
UAB_Thyme
Uncovering mechanisms of intellectual disability using zebrafish as a model.
Summer Thyme
The University of Alabama at Birmingham
Neurobiology
Biological and Biomedical Sciences
14
OSG Connect
748
DDPSC_Baxter
Genome-wide association analysis of elemental accumulation in the Maize Nested Association Mapping panel
Ivan Baxter
Donald Danforth Plant Science Center
Plant Genetics
Biological and Biomedical Sciences
14
OSG Connect
116
uchicago
General use Project for the University of Chicago
Robert William Gardner Jr
University of Chicago
Computation Institute
Multi-Science Community
14
OSG Connect
678
duke.ppsa
Theoretical underpinnings of macromolecular crystalization
Irem Altan
Duke University
Chemistry
Chemistry
15
Duke
647
UserSchool2016
Training account for 2016 User School
Christina Koch
University of Wisconsin-Madison
Computer Science
Training
14
OSG Connect
1063922570
PSU_Rechtsman
Laboratory for emergent phenomena and technology in the optical sciences
Mikael Rechtman
Pennsylvania State University
Physics
Physics
14
OSG Connect
60
duke-campus
Default project for new Duke users
Tom Milledge
Duke University
Scalable Computing Suport Center-OIT
Community Grid
15
Duke
219
cms.org.wayne
Wayne State University
Paul Karchin
Wayne State University
Physics
High Energy Physics
18
CMS Connect
796
IIT_Cheng
Developing high order invariant and equivariant graph neural networks for solving problems in various domains
Maggie Cheng
Illinois Institute of Technology
College of Computing
Mathematics
14
OSG Connect
494188212
USD_PHYS733
A course on Elementary Particle and Nuclear Physics at the University of South Dakota
Jing Liu
University of South Dakota
Physics
Elementary Particles
14
OSG Connect
811
Tutorial-PEARC21
PEARC21 tutorial
Christina Koch
Open Science Grid
OSGConnect
Computer and Information Science and Engineering
14
OSG Connect
668
SIUE_Staff
Staff at Southern Illinois University who centrally support research computing
David Chace
Southern Illinois University Edwardsville
Network and Systems Infrastructure
Multi-Science Community
14
OSG Connect
607710088
UF_Hirschfeld
Magnetic and toopological properties of line defects in multiband superconductors. use Bogoliubov-de Gennes equations
Peter Hirschfeld
University of Florida
Physics dept.
Physics
14
OSG Connect
716
Rice_AjoFranklin
Grid Analysis of Distributed Acoustic Sensing Datasets
Jonathan Ajo-Franklin
Rice University
Earth, Environmental, and Planetary Sciences
Earth and Ocean Sciences
14
OSG Connect
88
IceCube
IceCube is the world's largest neutrino detector. It is located at the South Pole and includes a cubic kilometer
of instrumented ice. IceCube searches for neutrinos from the most violent astrophysical sources: events like exploding stars, gamma
ray bursts, and cataclysmic phenomena involving black holes and neutron stars. The IceCube telescope is a powerful tool to search for
dark matter, and could reveal the new physical processes associated with the enigmatic origin of the highest energy particles in
nature. In addition, exploring the background of neutrinos produced in the atmosphere, IceCube studies the neutrinos themselves; their
energies far exceed those produced by accelerator beams.
Francis Halzen
University of Wisconsin-Madison
Physics
Astrophysics
14
OSG Connect
809
Canisius_Wood
My research is to study the proton hadronization by mining the CLAS6 data from Jefferson Lab.
Michael Wood
Canisius College
Physics
Nuclear Physics
14
OSG Connect
749
KSU_CIS625
KSU CIS625 Concurrent Software Systems
Daniel Andresen
Kansas State University
Computer Science
Computer Science
14
OSG Connect
209
cms.org.purdue
CMS Connect at Purdue University
Norbert Neumeister
Purdue University
Physics
High Energy Physics
18
CMS Connect
247
atlas.org.anl
ATLAS Connect team for Argonne National Laboratory
Robert William Gardner Jr
Argonne National Laboratory
Physics
High Energy Physics
16
ATLAS Connect
617
UCF_Wiegand
Predictions on Traffic with Deep Learning and Reinforcement Learning
Paul Wiegand
University of Central Florida
Intitute for Simulation and Training
Computer Science
14
OSG Connect
379
TG-MCB160069
Experiments have shown that co-translational phe
nomena can strongly influence protein function. A mechanistic understanding of co-translational phenomena such as nascent chain tension and protein misfolding can be gained with molecu
lar dynamics simulations using multi-scale models of ribosome-nascent chain complexes (RNCs). Using atomistic and coarse-grained models of RNCs, we will measure the magnitude of the mec
hanical force generated by co-translational folding, determine the effects of folding domain size and stability on this force, and investigate how codon translation rates can alter the
probability of folding and misfolding.
Edward O'Brien
Pennsylvania State University
Chemistry
Molecular and Structural Biosciences
13
OSG-XSEDE
240
cms.org.wisc
CMS Connect at University of Wisconsin
Wesley Smith
University of Wisconsin-Madison
Physics
High Energy Physics
18
CMS Connect
35
TG-OCE130029
Methods that integrate population sampling from multiple taxa into a single analysis are a much needed addition to the comparative phylogeographic toolkit. Here we present a statistical framework for multi-species analysis based on hierarchical approximate Bayesian computation (hABC) for inferring community dynamics and concerted demographic response. Detecting community response to climate change is an important issue with regards to how species have and will react to past and future events. Furthermore, whether species responded individualistically or in concert is at the center of related questions about the abiotic and biotic determinants of community assembly. This method combines multi-taxon genetic datasets into a single analysis to determine the proportion of a contemporary community that historically expanded in a temporally clustered pulse as well as when the pulse occurred. We will apply this method to 59 species in the Hawaiian Archipelago in order to examine community response of coral reef taxa to sea-level change in Hawaii. The method can accommodate dataset heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and utilizes borrowing strength from the simultaneous analysis of multiple species. This hABC framework used in a multi-taxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently, and can be used with a wide variety of comparative phylogeographic datasets as biota-wide DNA barcoding data sets accumulate.
Yvonne Chan
University of Hawaii at Manoa
Hawaii Institute of Marine Biology
Ocean Sciences
13
OSG-XSEDE
402
TRNG
Testing Random number Generators via parallel Testu01 package.
Asia Aljahdali
Florida State University
Computer Science
Computer and Information Science and Engineering
14
OSG Connect
490
gm2
Project entry corresponding to the gm2 VO (Muon g-2 at Fermilab).
Joe Boyd
Fermilab
N/A
High Energy Physics
9
Fermilab
452
EpiBrain
We are trying to better understand how networks evolve in the brain of animals and humans with epilepsy. We hope to leverage this information in the design of more effective electrical stimulation paradigms.
David Mogul
Illinois Institute of Technology
Biomedical Engineering
Neuroscience
14
OSG Connect
822
UWMadison_Bechtol
Searching for Dark Energy evidence via gravitational double-lens effects in massive astronomical objects
Keith Bechtol
University of Wisconsin-Madison
Physics
Astronomy
14
OSG Connect
175
BGAgenomics
This is a cyanobacteria genomics program
Sucheta Tripathy
Indian Institute of Chemical Biology
Structural Biology and Bioinformatics division
Bioinformatics
14
OSG Connect
763263391
Drexel_URCF
Accounts for Drexel University Research Computing Facility Staff; Information about our facility: https://drexel.edu/core-facilities/facilities/research-computing/
David Chin
Drexel University
University Research Computing Facility
Computer Sciences
14
OSG Connect
671
COVID19_LSUHSC_Chapple
Most Bayesian methods require Markov Chain Monte Carlo sampling (MCMC) to obtain posterior distributions, which can be used for statistical inference - and decision making during adaptive clinical trial designs. To justify any novel statistical method or adaptive design, extensive simulation studies must be conducted to demonstrate their effectiveness. Dr. Chapple recently used OSG to successfully revise a novel statistical method for survival analysis relevant to COVID-19. Such simulations, particularly for Bayesian adaptive clinical trials, can take a tremendous amount of time to run 1,000 or more simulations for a given scenario, and usually hundreds of scenarios are warranted to convince others of the trial’s benefit. Dr. Chapple has used 435 thousand core hours to develop clinical trial designs for testing safety of new agents in pediatric brain tumors, testing multiple COVID-19 therapies simultaneously, and determining optimal treatments based on patient subgroups. Without OSG, it would not have been possible to start enrolling patients in a 3-treatment armed COVID-19 trial at University Medical Center in New Orleans, LA. Based upon that success, Chapple will also demonstrate the same approach for 5 treatment arms, and also for subgroups (based on comorbidities, age, etc), and publish the trial design in a statistical journal.
Andrew Chapple
LSU School of Public Health
Biostatistics
Health
14
OSG Connect
815
UWMadison_Keles
statistical genomics
Sunduz Keles
University of Wisconsin-Madison
Biostatistics and Medical Informatics
Mathematics
14
OSG Connect
717
OregonState_Simon
Generation and Testing of Hypothetical Metal-Organic Frameworks
Cory Simon
Oregon State University
Chemical, Biological and Environmental Engineering
Physics
14
OSG Connect
230
cms.org.ttu
CMS Connect at Texas Tech University
Nural Akchurin
Texas Tech University
Physics
High Energy Physics
18
CMS Connect
395
IngaCFMID
We study how interactions between plants and their insect herbivores lead to the evolution of plant defenses, including plant's chemical defenses. In order to identify some of the many unknown compounds we have isolated via LC-MS from the tropical tree genus Inga (Fabaceae), we use in silico fragmentation to predict the ms/ms spectra for a given chemical structure using Competitive Fragmentation Modeling for Metabolite Identification (CFM-ID) (http://cfmid.wishartlab.com). This allows us to match observed ms/ms spectra with a theoretical library of known and predicted chemical structures.
Thomas A. Kursar
University of Utah
Biology
Biological Sciences
14
OSG Connect
687
wrench
WRENCH: Workflow Management System Simulation Workbench
Rafael Ferreira Da Silva
University of Southern California
ISI
Computer and Information Science and Engineering
9
ISI
297
atlas.wg.Top
ATLAS Connect team for Top
Robert William Gardner Jr
US ATLAS
Physics
High Energy Physics
16
ATLAS Connect
803
NDSU_Yellavajjala
A.I. Reinforcement Learning Algorithm
Ravi Kiran Yellavajjala
North Dakota State University
Civil and Environmental Engineering
Engineering
14
OSG Connect
795744068
UCSD_Goetz
Emerging machine learning (ML) models enable the design of atomistic interaction potentials for molecular simulations that are both accurate and computationally efficient. Training of these ML models requires a large number of reference data in form of energies and nuclear forces of relevant molecular conformations and intermolecular interactions. This project will compute accurate quantum mechanical reference energies and forces using density functional theory and coupled cluster theory of relevance for chemical and biomolecular simulations.
Andreas Goetz
University of California, San Diego
San Diego Supercomputing Center
Chemistry
14
OSG Connect
2050042360
Albany_DAES
Department of Atmospheric and Environmental Sciences at the University of Albany.
Ryan Torn
University of Albany
Department of Atmospheric Environmental Sciences
Atmospheric Sciences
14
OSG Connect
829
AMNH_Burbrink
This work explores systematics of snakes using genomic and ecological data.
Frank Burbrink
American Museum of Natural History
Herpetology
Biological Sciences
14
OSG Connect
690
USC_Deelman
Pegasus workflow management system - development and testing
Ewa Deelman
University of Southern California
Information Sciences Institute
Computer and Information Science and Engineering
9
ISI
566
WayneStateU_TDA
Topological Data Analysis of fMRI Signals during Learning: Function to Structure
Andrew Salch
Wayne State University
Mathmatics
Mathematics
14
OSG Connect
2064420708
UMassLowell_Laycock
Understanding the accretion and Stellar wind interaction in Black hole+massive star binary system.
Silas G. T. Laycock
University of Massachusetts Lowell
Department Of Physics
Astronomy and Astrophysics
14
OSG Connect
830
BC_Grubb
This project studies the implementation of a public policy that restricts gender-based pricing in the Chilean private health insurance system. For that matter, I will estimate how enrollees choose plans and how sensitive they are to prices in this market using a discrete choice demand model. With these estimates in hand, I will simulate how people choose plans once prices are restricted to be the same between men and women, and how the structure of the market, in terms of costs, changes after the implementation of the policy.
Michael Grubb
Boston College
Economics
Economics
14
OSG Connect
844
Purdue_Aggarwal
Our labs works towards developing efficient machine learning algorithms for real-world problems. Some of the applications that we focus on are social influence maximization, recommender systems, and ride-sharing and goods delivery.
Vaneet Aggarwal
Purdue University
Industrial Engineering
Computer Sciences
14
OSG Connect
232
cms.org.uic
CMS Connect at University of Illinois at Chicago
Nikos Varelas
University of Illinois Chicago
Physics
High Energy Physics
18
CMS Connect
516
PNGtemplate
This project aims at creating population-specific templates that target adolescent athletes, based on the T1-weighted images from Purdue Neurotrauma Group (PNG) longitudinal datasets.
Joseph Rispoli
Purdue University
Biomedical Engineering
Medical Imaging
14
OSG Connect
48328218
Princeton_Jamieson
studying channel modeling using AI/ML techniques. Ray tracing and improving upon 3GPP standardized channel models are our goals.
Kyle Jamieson
Princeton University
Princeton Advanced Wireless Systems Lab
Electrical, Electronic, and Communications
574
GRAPLEr
The GLEON Research And PRAGMA Lake Expedition (GRAPLE) is a collaborative effort between computer science and lake ecology researchers. It aims to improve our understanding and predictive capacity of the threats to the water quality of our freshwater resources, including climate change. GRAPLEr is a distributed computing system used to address the modeling needs of GRAPLE researchers. GRAPLEr integrates and applies overlay virtual network, high-throughput computing, and Web service technologies in a novel way. First, its user-level IP-over-P2P (IPOP) overlay network allows compute and storage resources distributed across independently-administered institutions (including private and public clouds) to be aggregated into a common virtual network, despite the presence of firewalls and network address translators. Second, resources aggregated by the IPOP virtual network run unmodified high-throughput computing middleware (HTCondor) to enable large numbers of model simulations to be executed concurrently across the distributed computing resources. Third, a Web service interface allows end users to submit job requests to the system using client libraries that integrate with the R statistical computing environment.
Shava Smallen
Pacific Rim Application and Grid Middleware Assembly (PRAGMA)
N/A
Ecological and Environmental Sciences
14
OSG Connect
593
UCAnschutz_Langner
Understanding efficiency losses due to data coarsening
Elizabeth Juarez-Colunga
University of Colorado Anschutz Medical Campus
Biostatistics and Medical Informatics
Biostatistics
14
OSG Connect
768
Villanova_Staff
Research Computing Staff at Villanova University
Aaron P. Wemhoff
Villanova University
Mechanical Engineering
Computer Sciences
14
OSG Connect
47
TG-ATM130015
The global distribution of precipitating auroral particles is a crucial input to models of the magnetosphere and the coupling between the magnetosphere-ionosphere. In particular, the spectral distributions which can be used to characterize the shape of precipitating electron spectra are equally important inputs to models and can be used provide information about the magnetospheric source regions of the precipitating particles. We detail the need for and the development of maps of characterized particle spectra and present a case for a resource request to aid with the development of these maps.
Phillip Anderson
University of Texas at Dallas
Physics
Atmospheric Sciences
13
OSG-XSEDE
340
AfricanSchool
A project for teaching the grid computing component of the African School of Physics.
Rob Quick
Indiana University
UITS
Education
14
OSG Connect
599
UWMadison_Gutierrez
Understanding crop exeriment design
Lucia Gutierrez
University of Wisconsin-Madison
Agronomy
Agronomy
14
OSG Connect
427
EMODIS-NDVI
processing EMODIS NDVI using HTC
Dayne Broderson
University of Alaska Fairbanks
Geographic Information Network of Alaska
Geographic Information Science
14
OSG Connect
140483721
PortlandState_OIT
Office of information technology staff at PDX
Gary Sandine
Portland State University
OIT
Computer Sciences
14
OSG Connect
1610528445
UNM_Gulisija
Develop theoretical models, statistical approaches, and computer simulations to elucidate mechanisms of rapid genetic adaptation to environmental change, such as due to global climate change or habitat invasions.
Davorka Gulisija
University of New Mexico
Department of Biology
Biological and Biomedical Sciences
14
OSG Connect
189400657
LBNL_Jensen
Spectral reconstruction of laser-driven secondary light sources
Kyle Jensen
Lawrence Berkeley National Laboratory
ATAP, BELLA Center
Physics
679
icarus
ICARUS, the worlds' first large liquid-argon neutrino detector
Carlo Rubbia
Fermilab
N/A
High Energy Physics
9
Fermilab
384667780
UMaine_Vel
Study the nonlinear elastic behavior of nanomaterials using a polynomial based constitutive equation to model the behavior of the materials.
Senthil S. Vel
University of Maine
Mechanical Engineering
Materials Science
14
OSG Connect
828
NIST_CTCMS
Staff in the Center for Theoretical and Computational Materials at the National Institute of Standards and Technology.
Andrew Reid
National Institute of Standards and Technology
Center for Theoretical and Computational Materials
Multi-Science Community
14
OSG Connect
727
UNL_Howard
Dimension Reduction Strategies for Genomic Prediction
Reka Howard
University of Nebraska-Lincoln
Statistics
Mathematics and Statistics
14
OSG Connect
702
UWMadison_Skala
Using neural networks to segment microscope cell images
Melissa Skala
University of Wisconsin-Madison
Medical Engineering
Medical Imaging
14
OSG Connect
2002587411
UCSD_Xu
Applying machine learning and causal inference methods to the analysis of biomedical data.
Ronghui (Lily) Xu
University of California, San Diego
Mathematics
Mathematics
14
OSG Connect
420
EvolCE
Multi-locus simulations under periodic environments.
Davorka Gulisija
University of Pennsylvania
Biology
Biological Sciences
14
OSG Connect
202
cms.org.ucsb
CMS Connect at University of California, Santa Barbara
Joe Incandela
University of California, Santa Barbara
Physics
High Energy Physics
18
CMS Connect
800
MIT_Akiyama
Developing computational imaging techniques in radio astronomy
Kazunori Akiyama
Massachusetts Institute of Technology
Haystack Observatory
Astronomy
14
OSG Connect
2039215356
UMiss_Gupta
We are studying the evolution of binary black holes and it would be great to try out the OS Pool facility through the AP40 cluster.
Anuradha Gupta
University of Mississippi
LIGO
Astronomy and Astrophysics
87
Proteomics
Bioinformatics methods for different proteomic applications in life sciences. Algorithm development for improving
mass-spectrometry based proteomic techniques.
Sam Volchenboum
University of Chicago
Computation Institute
Bioinformatics
14
OSG Connect
172
DemandSC
We estimate switching costs with aggregate data in the context of price wars and collusion to study how mergers and changes to market structure affect welfare under the different competitive scenarios
Fernando Luco
Texas A&M University
Economics
Economics
14
OSG Connect
375
molcryst
Quantum chemical and machine learning insights into supra-molecular organization of molecular crystals.
Olexandr Isayev
University of North Carolina at Chapel Hill
Chemistry
Chemistry
14
OSG Connect
739
Mines_CIARCStaff
Staff at the Cyberinfrastrucure and Advanced Research Computing, within central IT (ITS).
Matthew Ketterling
Colorado School of Mines
Cyberinfrastructure and Advanced Research Computing
Computer and Information Sciences
14
OSG Connect
653
Clemson_Sarupria
Ensemble-based simulations
Sapna Sarupria
Clemson University
Chemical and Biomolecular Engineering
Engineering
14
OSG Connect
1993491804
UWMadison_Pool
Population Genomics and the Genetic Basis of Adaptive Evolution - http://www.genetics.wisc.edu/user/338
John Pool
University of Wisconsin-Madison
Genomics & Genetics
Biological Sciences
8
ECFA
Simulate hundreds of millions of high-energy
proton proton collisions, which mimic the
collisions expected at the LHC in the coming
years. This simulated data is used to assess the
physics potential of potential detector upgrades,
allowing decision makers and funding agencies to
plan for the future.
Meenakshi Narain
Brown University
Physics
High Energy Physics
30
OSG
845
Stanford_Fletcher
Optimizing water resource planning decisions through simulating effects of climate change projections on models of city water supply portfolios.
Sarah Fletcher
Stanford University
Civil and Environmental Engineering
Engineering
14
OSG Connect
512
TG-TRA180032
Campus Champion for Wichita State University. I will use the allocation to help researchers at Wichita State University learn how to utilize HPC and HTC systems in their various research projects. My goal is to use this allocation to introduce XSEDE to students and faculty.
Terrance Figy
Wichita State University
ITS
Training
13
OSG-XSEDE
435
PSFmodeling
We need to use Monte-Carlo simulation to obtain the point spread function (PSF) kernels to be incorporated into our image reconstruction algorithm for more accurate image reconstruction
Paul Vaska
State University of New York at Stony Brook
Biomedical Engineering
Biological Sciences
14
OSG Connect
360
MedInf
Analysis of modern surgery presents many interesting computational challenges. The problems of access to data, data analysis, and interpretation of said analysis all present fundamental, unsolved difficulties to those in medical informatics. The focus of this project primarily involves data analysis where operations are still typically thought of holistically and conceptually, rather than algorithmically. This work is an attempt to change that by properly defining surgical procedures in a manner conducive to both education and analysis.
Alex Langerman
The University of Chicago
Otolaryngology
Medical Sciences
14
OSG Connect
483
Mapping
Spectroscopic maps are widely used in condensed-phase vibrational spectroscopic simulations. We aim to develop ab-initio-based maps for water, and more complex systems.
Liang Shi
University of California, Merced
Chemistry
Chemistry
14
OSG Connect
614480514
UCSD_Rao
Machine learning algorithms for signal processing and communications, particularly mmWave and medical imaging.
Bhaskar Rao
University of California, San Diego
Electrical and Computer Engineering
Computer and Information Sciences
14
Duke-QGP
Event-by-event simulations of relativistic heavy-ion collisions. QGP characterization via model-to-data comparison.
Steffen A. Bass
Duke University
Physics
Nuclear Physics
30
OSG
228
cms.org.rice
CMS Connect at Rice University
Jay Roberts
Rice University
Physics
High Energy Physics
18
CMS Connect
416
nsides
Using deep learning models to discover statistically significant drug effects using public drug surveillance datasets from the Federal Drug Administration.
Nicholas Tatonetti
Columbia University
Biomedical Informatics
Bioinformatics
14
OSG Connect
425231092
LSU_Wilson
The study of disorder effects in quantum materials and in far-from equilibrium quantum systems.
Justin Wilson
Louisiana State University
Physics and Astronomy
Physics
14
OSG Connect
705
UWMadison_Rui
Structure + behavior of genomes related to lymphoma
Lixin Rui
University of Wisconsin-Madison
Medicine
Health
14
OSG Connect
585
UWMadison_Parks
Brian Parks
University of Wisconsin-Madison
Nutritional Science
Nutritional Science
14
OSG Connect
40
TG-MCB090163
This proposal requests CPU time on XSEDE resources for research aimed at understanding assembly and pattern formation in biological and biomimetic systems. The first two subprojects will use coarse-grained simulations to explore two processes which are essential for replication of many viruses: the assembly of capsid proteins around RNA and the simultaneous assembly and budding of capsid proteins through lipid bilayers. The third subproject will study pattern formation and spontaneous flow in a far-from-equilibrium system containing microtubules and motor proteins studied by our experimental collaborators, the Dogic Lab at Brandeis. A common goal in each of the three subprojects is to reveal structural and dynamical information about key intermediates which are not accessible to experiments. The simulations of capsid assembly around RNA will be performed with the program HOOMD which enables great computational speedups on GPUs. The simulations of capsids assembling on lipid bilayers will use LAMMPS which affords excellent scaling for the large membranes being considered. The simulations of microtubules and motor proteins will use a self-written code optimized to characterize high aspect ratio, extensile bundles. Funding for Subprojects 1 & 2 is provided by NIH NIAID (R01AI080791) and Subproject 3 is funded by the NSF (NSF-MRSEC-0820492).
Michael Hagan
Brandeis University
Physics
Molecular and Structural Biosciences
13
OSG-XSEDE
572
TG-DMR190045
1D nanoconfined helium: A versatile platform for exploring Luttinger liquid physics
Adrian Del Maestro
University of Vermont
Physics
Condensed Matter Physics
13
OSG-XSEDE
1443979740
UWMadison_Kwan
Bioactive molecules from cultured and uncultured bacteria (https://kwanlab.github.io/)
Jason Kwan
University of Wisconsin-Madison
Pharmacy
Health
245
freesurfer
Brain image analysis with free surfer software
Donald Krieger
University of Pittsburgh
Department of Neurological Surgery
Neuroscience
14
OSG Connect
462
DataSaoPaulo
A project for teaching the grid computing component at Sao Paulo, Brazil
Rob Quick
Indiana University
UITS
Education
14
OSG Connect
392
TG-TRA120004
This allocation will be used to help researchers at Columbia University understand how to use XSEDE resources.
Rob Lane
Columbia University
Columbia University Information Techonology
Other
13
OSG-XSEDE
206
cms.org.fsu
CMS Connect at Florida State University
Todd Adams
Florida State University
Physics
High Energy Physics
18
CMS Connect
68661170
UTAustin_Shoemaker
Gravitational wave work for current and future gravitational wave detectors
Deirdre Shoemaker
University of Texas at Austin
Physics
Astronomy and Astrophysics
14
OSG Connect
929615245
Harvard_Wofsy
The goal is to measure methane emissions from major source regions in the US, in order to facilitate reduction of these emissions.
Steven Wofsy
Harvard University
Department of Earth and Planetary Sciences
Atmospheric Sciences
14
OSG Connect
254
atlas.org.harvard
ATLAS Connect team for Harvard University
Robert William Gardner Jr
Harvard University
Physics
High Energy Physics
16
ATLAS Connect
810
Tufts_Levin
The project uses a biophysical simulation engine (BETSE) to explore the parameter space of the bioelectrical dynamics of a cluster of somatic cells.
Michael Levin
Tufts University
Department of Biology
Biological and Biomedical Sciences
14
OSG Connect
537
UCIAtlas
University of California, Irvine Atlas Group
Anyes Taffard
University of California, Irvine
Physics
High Energy Physics
35
ATLAS
506
DiffCorr
Dynamics of electrons with different degree of correlations
Jacek Herbrych
University of Tennessee
Department of Physics and Astronomy
Computational Condensed Matter Physics
14
OSG Connect
408037770
NCSU_Hall
Studies of square shaped colloidal particles with internal magnetic dipoles. Objective is to discover the phase behavior of colloids under the presence and absence of a magnetic field.
Carol Hall
North Carolina State University
Department of Chemical and Biomolecular Engineering
Chemical Engineering
14
OSG Connect
619962250
GATech_Jezghani
Free neutron and nuclear isotope beta decay is a sensitive test of the Standard Model and probe for BSM physics that complements high-energy efforts such as those at the LHC. Precision efforts such as the Nab experiment at ORNL rely on high-statistics simulations to constrain error. More details can be seen at https://nab.phys.virginia.edu.
Aaron Jezghani
Georgia Institute of Technology
PACE
Physics
14
OSG Connect
774
TG-DDM160003
OSG SP - Allocation for Service Provider testing and integration
Mats Rynge
University of Southern California
Information Sciences Institute
Computer and Computation Research
13
OSG-XSEDE
1409904489
UIowa_Villarini
The research will focus broadly on flood hydrology, extreme events, hydroloclimatology, and climate predictions. It will be done by the processing of spatial and temporal datasets and running simple statistical models.
Gabriele Villarini
University of Iowa
Civil and Environmental Engineering
Civil Engineering
14
OSG Connect
787
UMCES_Fitzpatrick
Using machine learning and other methods to modeling the vulnerability of species to climate change.
Matthew Fitzpatrick
University of Maryland Center for Environmental Science
Appalachian Lab
Biological Sciences
14
OSG Connect
273
atlas.org.ucsc
ATLAS Connect team for University of California, Santa Cruz
Robert William Gardner Jr
University of California, Santa Cruz
Physics
High Energy Physics
16
ATLAS Connect