Centers & Labs

RIKEN Center for Computational Science

High Performance Artificial Intelligence Systems Research Team

Team Leader: Satoshi Matsuoka (Ph.D.)
Satoshi  Matsuoka(Ph.D.)

The High Performance Artificial Intelligence Systems Research Team is an R-CCS laboratory focusing on convergence of HPC and AI, namely high performance systems, software, and algorithms research for artificial intelligence/machine learning. In collaboration with other research institutes in HPC and AI-related research in Japan as well as globally, it seeks to develop next-generation AI technology that will utilize state-of-the-art high-performance computation facilities, including the post-K. Specifically, we conduct research on next-generation AI systems by focusing on the following topics:

  1. Extreme speedup and scalability of deep learning:
    Achieve extreme scalability of deep learning in large-scale supercomputing environments including the post-K, extending the latest algorithms and frameworks for deep learning.
  2. Performance analysis of deep learning:
    Accelerate computational kernels for AI over the state-of-the-art hardware architectures by analyzing algorithms for deep learning and other machine learning/AI, measuring their performance and constructing their performance models.
  3. Acceleration of modern AI algorithms:
    Accelerate advanced AI algorithms, such as ultra-deep neural networks and high-resolution GAN over images, those that require massive computational resources, using extreme-scale deep learning systems.
  4. Acceleration of HPC algorithms using machine learning:
    Accelerate HPC algorithms and applications using empirical models based on machine learning.

Main Research Field


High Performance Computing / High Performance Computing / Computer Architecture


  • High Performance Artificial Intelligence Systems
  • Scalable Deep Learning
  • Performance Modeling of AI Systems e.g. Deep Learning
  • Acceleration of Advanced Deep Learning Algorithms
  • Convergence of AI and Simulation

Selected Publications

Papers with an asterisk(*) are based on research conducted outside of RIKEN.
  1. *Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Rio Yokota, and Satoshi Matsuoka.:
    “Large-scale Distributed Second-order Optimization Using Kronecker-factored Approximate Curvature for Deep Convolutional Neural Networks”
    2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), to appear.
  2. *Yusuke Nagasaka, Akira Nukada, Ryosuke Kojima, and Satoshi Matsuoka.:
    “Batched Sparse Matrix Multiplication for Accelerating Graph Convolutional Networks”
    The 19th Annual IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing (CCGrid 2019), to appear.
  3. *Shweta Salaria, Aleksandr Drozd, Artur Podobas, and Satoshi Matsuoka.:
    "Learning Neural Representations for Predicting GPU Performance"
    ISC High Performance 2019 (ISC'19), to appear.
  4. *Pak Markthub, and Mehmet E. Belviranli, Seyong Lee, Jeffrey Vetter, and Satoshi Matsuoka.:
    "DRAGON: Breaking GPU Memory Capacity Limits with Direct NVM Access"
    Proceedings of the ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'18), pp 32:1--32:13.
  5. *Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, and Satoshi Matsuoka.:
    "Accelerating Deep Learning Frameworks with Micro-batches"
    2018 IEEE International Conference on Cluster Computing (CLUSTER 2018) pp 402-412.
  6. *Yosuke Oyama, Akihiro Nomura, Ikuro Sato, Hiroki Nishimura, Yukimasa Tamatsu, and Satoshi Matsuoka.:
    “Predicting Statistics of Asynchronous SGD Parameters for a Large-Scale Distributed Deep Learning System on GPU Supercomputers”
    2016 IEEE International Conference on Big Data (Big Data 2016), pp. 66-75.

Contact information

RIKEN Center for Computational Science (R-CCS)
7-1-26 Minatojima-minami-machi,
Kobe, Hyogo,
Japan 650-0047
Tel: +81-(0)78-940-5580
Fax: +81-(0)78-304-4957

Email: matsu [at]

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