S
Satoshi Matsuoka
Researcher at Tokyo Institute of Technology
Publications - 28
Citations - 1015
Satoshi Matsuoka is an academic researcher from Tokyo Institute of Technology. The author has contributed to research in topics: CUDA & Deep learning. The author has an hindex of 6, co-authored 28 publications receiving 847 citations. Previous affiliations of Satoshi Matsuoka include Association for Computing Machinery & Lawrence Berkeley National Laboratory.
Papers
More filters
Journal ArticleDOI
The International Exascale Software Project roadmap
Jack Dongarra,Pete Beckman,Terry Moore,Patrick Aerts,Giovanni Aloisio,Jean-Claude Andre,David Barkai,Jean-Yves Berthou,Taisuke Boku,Bertrand Braunschweig,Franck Cappello,Barbara Chapman,Xuebin Chi,Alok Choudhary,Sudip S. Dosanjh,Thom H. Dunning,Sandro Fiore,Al Geist,Bill Gropp,Robert W. Harrison,Mark Hereld,Michael A. Heroux,Adolfy Hoisie,Koh Hotta,Zhong Jin,Yutaka Ishikawa,Fred Johnson,Sanjay Kale,Richard Kenway,David E. Keyes,Bill Kramer,Jesús Labarta,Alain Lichnewsky,Thomas Lippert,Bob Lucas,Barney Maccabe,Satoshi Matsuoka,Paul Messina,Peter Michielse,Bernd Mohr,Matthias S. Mueller,Wolfgang E. Nagel,Hiroshi Nakashima,Michael E. Papka,Daniel A. Reed,Mitsuhisa Sato,Edward Seidel,John Shalf,David Skinner,Marc Snir,Thomas Sterling,Rick Stevens,Frederick H. Streitz,Bob Sugar,Shinji Sumimoto,William Tang,John Taylor,Rajeev Thakur,Anne E. Trefethen,Mateo Valero,Aad J. van der Steen,Jeffrey S. Vetter,Peg Williams,Robert W. Wisniewski,Katherine Yelick +64 more
TL;DR: The work of the community to prepare for the challenges of exascale computing is described, ultimately combing their efforts in a coordinated International Exascale Software Project.
Journal ArticleDOI
Big data and extreme-scale computing: Pathways to Convergence-Toward a shaping strategy for a future software and data ecosystem for scientific inquiry
Mark Asch,Terry Moore,Rosa M. Badia,Micah Beck,Pete Beckman,T. Bidot,François Bodin,Franck Cappello,Alok Choudhary,B R de Supinski,Ewa Deelman,Jack Dongarra,Anshu Dubey,Geoffrey C. Fox,H. Fu,S. Girona,William Gropp,Michael A. Heroux,Yutaka Ishikawa,Kate Keahey,David E. Keyes,William Kramer,J. F. Lavignon,Yi Lu,Satoshi Matsuoka,B. Mohr,Daniel A. Reed,S. Requena,J. Saltz,Thomas C. Schulthess,Rick Stevens,Martin Swany,Alexander S. Szalay,William Tang,G. Varoquaux,J. P. Vilotte,Robert W. Wisniewski,Zhiwei Xu,I. Zacharov +38 more
TL;DR: It is argued that the rapid proliferation of digital data generators, the unprecedented growth in the volume and diversity of the data they generate, and the intense evolution of the methods for analyzing and using that data are radically reshaping the landscape of scientific computing.
Proceedings ArticleDOI
AN5D: Automated Stencil Framework for High-Degree Temporal Blocking on GPUs
TL;DR: AN5D is proposed, an automated stencil framework which is capable of automatically transforming and optimizing stencil patterns in a given C source code, and generating corresponding CUDA code and Parameter tuning in the framework is guided by the performance model.
Proceedings ArticleDOI
AN5D: automated stencil framework for high-degree temporal blocking on GPUs
TL;DR: AN5D as discussed by the authors automatically transforms and optimizes stencil patterns in a given C source code, and generates corresponding CUDA code for stencil computation on a given CUDA architecture.
Proceedings ArticleDOI
A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels.
TL;DR: In this paper, a systolic model that shifts partial sums by CUDA warp primitives for the computation is proposed to operate on regular kernels running on CUDA-enabled GPUs.