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Peter Mendygral
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2020 – today
- 2023
- [c5]Julius Donnert, Lindsey Gordon, Christopher Nolting, Peter Mendygral:
WisdomWombat: A polyglot dataflow CFD code using Python and Dragon. SC Workshops 2023: 641-643 - [c4]Nick Radcliffe, Kent Lee, Pete Mendygral:
Dragon Proxy Runtimes and Multi-system Workflows. SC Workshops 2023: 648-651 - 2021
- [c3]Sudheer Chunduri, Kevin Harms, Taylor L. Groves, Peter Mendygral, Justs Zarins, Michèle Weiland, Yasaman Ghadar:
Performance Evaluation of Adaptive Routing on Dragonfly-based Production Systems. IPDPS 2021: 340-349
2010 – 2019
- 2019
- [j2]Thorsten Kurth, Mikhail Smorkalov, Peter Mendygral, Srinivas Sridharan, Amrita Mathuriya:
TensorFlow at Scale: Performance and productivity analysis of distributed training with Horovod, MLSL, and Cray PE ML. Concurr. Comput. Pract. Exp. 31(16) (2019) - [c2]Sudheer Chunduri, Taylor L. Groves, Peter Mendygral, Brian Austin, Jacob Balma, Krishna Kandalla, Kalyan Kumaran, Glenn K. Lockwood, Scott Parker, Steven Warren, Nathan Wichmann, Nicholas J. Wright:
GPCNeT: designing a benchmark suite for inducing and measuring contention in HPC networks. SC 2019: 42:1-42:33 - 2018
- [j1]Douglas Doerfler, Brian Austin, Brandon Cook, Jack Deslippe, Krishna Kandalla, Peter Mendygral:
Evaluating the networking characteristics of the Cray XC-40 Intel Knights Landing-based Cori supercomputer at NERSC. Concurr. Comput. Pract. Exp. 30(1) (2018) - [c1]Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Kärnä, Diana Moise, Simon J. Pennycook, Kristyn J. Maschhoff, Jason Sewall, Nalini Kumar, Shirley Ho, Michael F. Ringenburg, Prabhat, Victor W. Lee:
CosmoFlow: using deep learning to learn the universe at scale. SC 2018: 65:1-65:11 - [i1]Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Karna, Diana Moise, Simon J. Pennycook, Kristyn J. Maschhoff, Jason Sewall, Nalini Kumar, Shirley Ho, Michael F. Ringenburg, Prabhat, Victor W. Lee:
CosmoFlow: Using Deep Learning to Learn the Universe at Scale. CoRR abs/1808.04728 (2018)
Coauthor Index
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