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Myths and Legends in High-Performance Computing


Jan 06, 2023
Satoshi Matsuoka, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Torsten Hoefler

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MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems


Oct 26, 2021
Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey 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

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Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA


Aug 26, 2020
Mohamed Wahib, Haoyu Zhang, Truong Thao Nguyen, Aleksandr Drozd, Jens Domke, Lingqi Zhang, Ryousei Takano, Satoshi Matsuoka

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* ACM/IEEE Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'20) 

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The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism


Jul 25, 2020
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen

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* 12 pages, 10 figures 

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Second-order Optimization Method for Large Mini-batch: Training ResNet-50 on ImageNet in 35 Epochs


Dec 05, 2018
Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Rio Yokota, Satoshi Matsuoka

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* 10 pages, 7 figures 

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μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching


Apr 13, 2018
Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka

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* 11 pages, 14 figures. Part of the content have been published in IPSJ SIG Technical Report, Vol. 2017-HPC-162, No. 22, pp. 1-9, 2017. (DOI: http://id.nii.ac.jp/1001/00184814

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