Yosuke Oyama

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 12

Top Topics

Weakly Supervised

Learning Frameworks

Massively Parallel

Top Venues

Publications

Yosuke Oyama, Akihiro Tabuchi, Atsushi Tokuhisa
Accelerating AlphaFold2 Inference of Protein Three-Dimensional Structure on the Supercomputer Fugaku. FlexScience@HPDC (2023)
Yosuke Oyama, Takumi Honda, Atsushi Ishikawa, Koichi Shirahata
Accelerating Hybrid DFT Simulations Using Performance Modeling on Supercomputers. CCGrid (2023)
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism. IEEE Trans. Parallel Distributed Syst. 32 (7) (2021)
Akihiko Kasagi, Masahiro Asaoka, Akihiro Tabuchi, Yosuke Oyama, Takumi Honda, Yasufumi Sakai, Thang Dang, Tsuguchika Tabaru
Efficient and Large Scale Pre-training Techniques for Japanese Natural Language Processing. CANDAR (2021)
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 Ramakrishniah, 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
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35 (6) (2021)
Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws? IPDPS (2021)
Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws? CoRR (2020)
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism. CoRR (2020)
Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka
Accelerating Deep Learning Frameworks with Micro-Batches. CLUSTER (2018)
Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka
μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching. CoRR (2018)
Ikuro Sato, Ryo Fujisaki, Yosuke Oyama, Akihiro Nomura, Satoshi Matsuoka
Asynchronous, Data-Parallel Deep Convolutional Neural Network Training with Linear Prediction Model for Parameter Transition. ICONIP (2) (2017)
Yosuke Oyama, Akihiro Nomura, Ikuro Sato, Hiroki Nishimura, Yukimasa Tamatsu, Satoshi Matsuoka
Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers. IEEE BigData (2016)