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Yosuke Oyama

Tokyo Institute of Technology

12

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54

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

2021 IPDPS | International Parallel and Distributed Processing Symposium
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Co-design Center for Exascale Machine Learning Technologies (ExaLearn):

2021 International Journal of High Performance Computing Applications
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The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism

2021 IEEE Transactions on Parallel and Distributed Systems
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The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism

2020 arXiv: Distributed, Parallel, and Cluster Computing
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Matrix Engines for High Performance Computing:A Paragon of Performance or Grasping at Straws?

2020 arXiv: Distributed, Parallel, and Cluster Computing
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mu-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching

2018 arXiv: Learning
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Asynchronous, Data-Parallel Deep Convolutional Neural Network Training with Linear Prediction Model for Parameter Transition

2017 ICONIP | International Conference on Neural Information Processing
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Connection Formula of Basic Hypergeometric Series rφr-1(0; b; q, x)

2017
- Yosuke Oyama
- yousuke ooyama
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Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers

2016 Big Data | International Conference on Big Data
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燃料電池用セパレータの成形研究機 SEPICS-300

2003 Seikei-kakou
- Yosuke Oyama
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