Yosuke Oyama

According to our database, Yosuke Oyama authored at least 10 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Accelerating AlphaFold2 Inference of Protein Three-Dimensional Structure on the Supercomputer Fugaku.

Yosuke Oyama, Akihiro Tabuchi, Atsushi Tokuhisa

Proceedings of the 13th Workshop on AI and Scientific Computing at Scale using Flexible Computing, 2023

Accelerating Hybrid DFT Simulations Using Performance Modeling on Supercomputers.

Yosuke Oyama, Takumi Honda, Atsushi Ishikawa, Koichi Shirahata

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2021

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

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

IEEE Trans. Parallel Distributed Syst., 2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).

Francis J. Alexander, James A. 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

Int. J. High Perform. Comput. Appl., 2021

Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws?

Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka

Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021

Efficient and Large Scale Pre-training Techniques for Japanese Natural Language Processing.

Akihiko Kasagi, Masahiro Asaoka, Akihiro Tabuchi, Yosuke Oyama, Takumi Honda, Yasufumi Sakai, Thang Dang, Tsuguchika Tabaru

Proceedings of the Ninth International Symposium on Computing and Networking, 2021

2018

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

Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka

CoRR, 2018

Accelerating Deep Learning Frameworks with Micro-Batches.

Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka

Proceedings of the IEEE International Conference on Cluster Computing, 2018

2017

Asynchronous, Data-Parallel Deep Convolutional Neural Network Training with Linear Prediction Model for Parameter Transition.

Ikuro Sato, Ryo Fujisaki, Yosuke Oyama, Akihiro Nomura, Satoshi Matsuoka

Proceedings of the Neural Information Processing - 24th International Conference, 2017

2016

Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers.

Yosuke Oyama, Akihiro Nomura, Ikuro Sato, Hiroki Nishimura, Yukimasa Tamatsu, Satoshi Matsuoka

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016