Yosuke Oyama

13 papers A 1B 1C 1Journal 6Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
LaMM: Semi-Supervised Pre-Training of Large-Scale Materials Models.
CoRR
Yosuke Oyama, Yusuke Majima, Eiji Ohta, Yasufumi Sakai
2023 — conf
Accelerating AlphaFold2 Inference of Protein Three-Dimensional Structure on the Supercomputer Fugaku.
FlexScience@HPDC
Yosuke Oyama, Akihiro Tabuchi, Atsushi Tokuhisa
2023 B conf
Accelerating Hybrid DFT Simulations Using Performance Modeling on Supercomputers.
CCGrid
Yosuke Oyama, Takumi Honda, Atsushi Ishikawa, Koichi Shirahata
2021 J jnl
Co-design Center for Exascale Machine Learning Technologies (ExaLearn).
Int. J. High Perform. Comput. Appl.
Francis J. Alexander, James Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon
2021 — conf
Efficient and Large Scale Pre-training Techniques for Japanese Natural Language Processing.
CANDAR
Akihiko Kasagi, Masahiro Asaoka, Akihiro Tabuchi, Yosuke Oyama, Takumi Honda, Yasufumi Sakai, Thang Dang, Tsuguchika Tabaru
2021 A conf
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws?
IPDPS
Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka
2021 J jnl
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism.
IEEE Trans. Parallel Distributed Syst.
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
2020 J jnl
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws?
CoRR
Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka
2020 J jnl
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism.
CoRR
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
2018 C conf
Accelerating Deep Learning Frameworks with Micro-Batches.
CLUSTER
Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka
2018 J jnl
μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching.
CoRR
Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka
2017 — conf
Asynchronous, Data-Parallel Deep Convolutional Neural Network Training with Linear Prediction Model for Parameter Transition.
ICONIP (2)
Ikuro Sato, Ryo Fujisaki, Yosuke Oyama, Akihiro Nomura, Satoshi Matsuoka
2016 — conf
Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers.
IEEE BigData
Yosuke Oyama, Akihiro Nomura, Ikuro Sato, Hiroki Nishimura, Yukimasa Tamatsu, Satoshi Matsuoka