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2020 – today
- 2024
[i9]Shashank Subramanian, Ermal Rrapaj, Peter Harrington, Smeet Chheda, Steven Farrell, Brian Austin, Samuel Williams, Nicholas J. Wright, Wahid Bhimji:
Comprehensive Performance Modeling and System Design Insights for Foundation Models. CoRR abs/2410.00273 (2024)- 2023
- [j2]Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell
, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant:
The Tracking Machine Learning Challenge: Throughput Phase. Comput. Softw. Big Sci. 7(1): 1 (2023) - [j1]Chunhui Li, Benjamin Gilbert, Steven Farrell, Piotr Zarzycki:
Rapid Prediction of a Liquid Structure from a Single Molecular Configuration Using Deep Learning. J. Chem. Inf. Model. 63(12): 3742-3750 (2023) - [i8]Ryan Liu, Paolo Calafiura, Steven Farrell, Xiangyang Ju, Daniel Thomas Murnane, Tuan Minh Pham:
Hierarchical Graph Neural Networks for Particle Track Reconstruction. CoRR abs/2303.01640 (2023) - 2022
- [i7]Xiangyang Ju, Yunsong Wang, Daniel Murnane, Nicholas Choma, Steven Farrell, Paolo Calafiura:
Benchmarking GPU and TPU Performance with Graph Neural Networks. CoRR abs/2210.12247 (2022) - 2021
- [c5]Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin:
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC 2021: 33-45 - [c4]Khaled Z. Ibrahim, Tan Nguyen, Hai Ah Nam, Wahid Bhimji, Steven Farrell, Leonid Oliker, Michael Rowan, Nicholas J. Wright, Samuel Williams:
Architectural Requirements for Deep Learning Workloads in HPC Environments. PMBS 2021: 7-17 - [c3]Charlene Yang, Yunsong Wang, Thorsten Kurth, Steven Farrell, Samuel Williams:
Hierarchical Roofline Performance Analysis for Deep Learning Applications. SAI (2) 2021: 473-491 - [i6]Xiangyang Ju, Daniel Murnane, Paolo Calafiura, Nicholas Choma, Sean Conlon, Steven Farrell, Yaoyuan Xu, Maria Spiropulu, Jean-Roch Vlimant, Adam Aurisano, Jeremy Hewes, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Markus Atkinson, Mark S. Neubauer, Gage DeZoort, Savannah Thais, Aditi Chauhan, Alex Schuy, Shih-Chieh Hsu, Alexandra Ballow, Alina Lazar:
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. CoRR abs/2103.06995 (2021) - [i5]Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant:
The Tracking Machine Learning challenge : Throughput phase. CoRR abs/2105.01160 (2021) - [i4]Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin:
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR abs/2110.11466 (2021) - 2020
- [c2]Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams:
Time-Based Roofline for Deep Learning Performance Analysis. DLS@SC 2020: 10-19 - [i3]Nicholas Choma, Daniel Murnane, Xiangyang Ju, Paolo Calafiura, Sean Conlon, Steven Farrell, Prabhat, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Panagiotis Spentzouris, Jean-Roch Vlimant, Maria Spiropulu, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy L. Usher:
Track Seeding and Labelling with Embedded-space Graph Neural Networks. CoRR abs/2007.00149 (2020) - [i2]Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams:
Time-Based Roofline for Deep Learning Performance Analysis. CoRR abs/2009.04598 (2020) - [i1]Yunsong Wang, Charlene Yang, Steven Farrell, Thorsten Kurth, Samuel Williams:
Hierarchical Roofline Performance Analysis for Deep Learning Applications. CoRR abs/2009.05257 (2020)
2010 – 2019
- 2018
- [c1]Paolo Calafiura, Steven Farrell, Heather M. Gray, Jean-Roch Vlimant, Vincenzo Innocente, Andreas Salzburger, Sabrina Amrouche, Tobias Golling, Moritz Kiehn, Victor Estrade, Cécile Germain, Isabelle Guyon, Ed Moyse, David Rousseau, Yetkin Yilmaz, Vladimir Vava Gligorov, Mikhail Hushchyn, Andrey Ustyuzhanin:
TrackML: A High Energy Physics Particle Tracking Challenge. eScience 2018: 344
Coauthor Index
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