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2020 – today
- 2024
[i3]Sanjif Shanmugavelu, Mathieu Taillefumier, Christopher Culver, Oscar R. Hernandez, Mark Coletti, Ada Sedova:
Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications. CoRR abs/2408.05148 (2024)- 2023
- [j6]Russell B. Davidson
, Mark Coletti, Mu Gao, Bryan Piatkowski, Avinash Sreedasyam, Farhan Quadir, David J. Weston, Jeremy Schmutz, Jianlin Cheng, Jeffrey Skolnick, Jerry M. Parks, Ada Sedova:
Predicted structural proteome of Sphagnum divinum and proteome-scale annotation. Bioinform. 39(8) (2023) - [j5]Darren J. Hsu, Russell B. Davidson, Ada Sedova, Jens Glaser:
tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking. J. Chem. Inf. Model. 63(11): 3438-3447 (2023) - [c11]Mark Coletti, Ada Sedova, Rajni Chahal, Luke Gibson, Santanu Roy, Vyacheslav Bryantsev:
Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II. ICPP Workshops 2023: 172-179 - 2022
- [j4]Russell B. Davidson, Jess Woods, T. Chad Effler, Mathialakan Thavappiragasam, Julie C. Mitchell, Jerry M. Parks, Ada Sedova:
OpenMDlr: parallel, open-source tools for general protein structure modeling and refinement from pairwise distances. Bioinform. 38(12): 3297-3298 (2022) - [c10]Mathialakan Thavappiragasam, Wael R. Elwasif, Ada Sedova:
Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms? CCGRID 2022: 975-984 - [c9]Mu Gao, Mark Coletti, Russell B. Davidson, Ryan Prout, Subil Abraham, Benjamín Hernández, Ada Sedova:
Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer. IPDPS Workshops 2022: 206-215 - [i2]Mathialakan Thavappiragasam, Wael R. Elwasif, Ada Sedova:
Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms? CoRR abs/2203.02096 (2022) - 2021
- [j3]Josh Vincent Vermaas, Ada Sedova, Matthew B. Baker, Swen Boehm, David M. Rogers, Jeff Larkin, Jens Glaser, Micholas Dean Smith, Oscar R. Hernandez, Jeremy C. Smith:
Supercomputing Pipelines Search for Therapeutics Against COVID-19. Comput. Sci. Eng. 23(1): 7-16 (2021) - [j2]Jens Glaser, Josh Vincent Vermaas, David M. Rogers, Jeff Larkin, Scott LeGrand, Swen Boehm, Matthew B. Baker, Aaron Scheinberg, Andreas F. Tillack, Mathialakan Thavappiragasam, Ada Sedova, Oscar R. Hernandez:
High-throughput virtual laboratory for drug discovery using massive datasets. Int. J. High Perform. Comput. Appl. 35(5) (2021) - [c8]Russell B. Davidson, Mathialakan Thavappiragasam, T. Chad Effler, Jess Woods, Dwayne A. Elias, Jerry M. Parks, Ada Sedova:
Modeling protein structures from predicted contacts with modern molecular dynamics potentials: accuracy, sensitivity, and refinement. BCB 2021: 21:1-21:10 - [c7]Mathialakan Thavappiragasam, Vivek Kale, Oscar R. Hernandez, Ada Sedova:
Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs. BIBM 2021: 1992-1999 - [c6]Mu Gao, Peik Lund-Andersen, Alex Morehead, Sajid Mahmud, Chen Chen, Xiao Chen, Nabin Giri, Raj S. Roy, Farhan Quadir, T. Chad Effler, Ryan Prout, Subil Abraham, Wael R. Elwasif, Nicholas Quentin Haas, Jeffrey Skolnick, Jianlin Cheng, Ada Sedova:
High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function. MLHPC@SC 2021: 46-57 - [i1]Alex Morehead, Chen Chen, Ada Sedova, Jianlin Cheng:
DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction. CoRR abs/2106.04362 (2021) - 2020
- [j1]Atanu Acharya, Rupesh Agarwal, Matthew B. Baker, Jérôme Baudry, Debsindhu Bhowmik, Swen Böhm, Kendall G. Byler, Sam Yen-Chi Chen, Leighton Coates, Connor J. Cooper, Omar Demerdash, Isabella Daidone, John D. Eblen, Sally R. Ellingson, Stefano Forli, Jens Glaser, James C. Gumbart, John Gunnels, Oscar R. Hernandez, Stephan Irle, Daniel W. Kneller, Andrey Kovalevsky, Jeffrey M. Larkin, Travis J. Lawrence, Scott LeGrand, Shih-Hsien Liu, Julie C. Mitchell, Gilchan Park, Jerry M. Parks, Anna Pavlova, Loukas Petridis, Duncan Poole, Line Pouchard, Arvind Ramanathan, David M. Rogers, Diogo Santos-Martins, Aaron Scheinberg, Ada Sedova, Yue Shen, Jeremy C. Smith, Micholas Dean Smith, Carlos Soto, Aristides Tsaris, Mathialakan Thavappiragasam, Andreas F. Tillack, Josh Vincent Vermaas, Van Quan Vuong, Junqi Yin, Shinjae Yoo, Mai Zahran, Laura Zanetti Polzi:
Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. J. Chem. Inf. Model. 60(12): 5832-5852 (2020) - [c5]Scott LeGrand, Aaron Scheinberg, Andreas F. Tillack, Mathialakan Thavappiragasam, Josh Vincent Vermaas, Rupesh Agarwal, Jeff Larkin, Duncan Poole, Diogo Santos-Martins, Leonardo Solis-Vasquez, Andreas Koch, Stefano Forli, Oscar R. Hernandez, Jeremy C. Smith, Ada Sedova:
GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research. BCB 2020: 43:1-43:10 - [c4]Mathialakan Thavappiragasam, Aaron Scheinberg, Wael R. Elwasif, Oscar R. Hernandez, Ada Sedova:
Performance Portability of Molecular Docking Miniapp On Leadership Computing Platforms. P3HPC@SC 2020: 36-44
2010 – 2019
- 2019
- [c3]John R. Ossyra, Ada Sedova, Arnold N. Tharrington, Frank Noé, Cecilia Clementi, Jeremy C. Smith:
Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer. ISC Workshops 2019: 397-417 - [c2]John R. Ossyra, Ada Sedova, Matthew B. Baker, Jeremy C. Smith:
Highly Interactive, Steered Scientific Workflows on HPC Systems: Optimizing Design Solutions. ISC Workshops 2019: 514-527 - 2018
- [c1]Ada Sedova, Andreas F. Tillack, Arnold N. Tharrington:
Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation. WACCPD@SC 2018: 22-47
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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