| Physis: an implicitly parallel programming model for stencil computations on large-scale GPU-accelerated supercomputers N Maruyama, T Nomura, K Sato, S Matsuoka Proceedings of 2011 International Conference for High Performance Computing …, 2011 | 259 | 2011 |
| Design and modeling of a non-blocking checkpointing system K Sato, N Maruyama, K Mohror, A Moody, T Gamblin, BR de Supinski, ... SC'12: Proceedings of the International Conference on High Performance …, 2012 | 146 | 2012 |
| An ephemeral burst-buffer file system for scientific applications T Wang, K Mohror, A Moody, K Sato, W Yu SC'16: Proceedings of the International Conference for High Performance …, 2016 | 142 | 2016 |
| Exploration of lossy compression for application-level checkpoint/restart N Sasaki, K Sato, T Endo, S Matsuoka 2015 IEEE international parallel and distributed processing symposium, 914-922, 2015 | 114 | 2015 |
| A user-level infiniband-based file system and checkpoint strategy for burst buffers K Sato, K Mohror, A Moody, T Gamblin, BR De Supinski, N Maruyama, ... 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2014 | 80 | 2014 |
| Entropy-aware I/O pipelining for large-scale deep learning on HPC systems Y Zhu, F Chowdhury, H Fu, A Moody, K Mohror, K Sato, W Yu 2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation …, 2018 | 70 | 2018 |
| Scalable multi-gpu 3-d fft for tsubame 2.0 supercomputer A Nukada, K Sato, S Matsuoka SC'12: Proceedings of the International Conference on High Performance …, 2012 | 54 | 2012 |
| A model-based algorithm for optimizing i/o intensive applications in clouds using vm-based migration K Sato, H Sato, S Matsuoka 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid …, 2009 | 44 | 2009 |
| Energy-aware I/O optimization for checkpoint and restart on a NAND flash memory system T Saito, K Sato, H Sato, S Matsuoka Proceedings of the 3rd Workshop on Fault-tolerance for HPC at Extreme Scale …, 2013 | 41 | 2013 |
| Fmi: Fault tolerant messaging interface for fast and transparent recovery K Sato, A Moody, K Mohror, T Gamblin, BR de Supinski, N Maruyama, ... 2014 IEEE 28th International Parallel and Distributed Processing Symposium …, 2014 | 39 | 2014 |
| Semi-synchronous federated learning protocol with dynamic aggregation in internet of vehicles F Liang, Q Yang, R Liu, J Wang, K Sato, J Guo IEEE Transactions on Vehicular Technology 71 (5), 4677-4691, 2022 | 37 | 2022 |
| Clock delta compression for scalable order-replay of non-deterministic parallel applications K Sato, DH Ahn, I Laguna, GL Lee, M Schulz Proceedings of the International Conference for High Performance Computing …, 2015 | 29 | 2015 |
| MLPerf™ HPC: A holistic benchmark suite for scientific machine learning on HPC systems S Farrell, M Emani, J Balma, L Drescher, A Drozd, A Fink, G Fox, D Kanter, ... 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing …, 2021 | 25 | 2021 |
| Direct-fuse: Removing the middleman for high-performance fuse file system support Y Zhu, T Wang, K Mohror, A Moody, K Sato, M Khan, W Yu Proceedings of the 8th International Workshop on Runtime and Operating …, 2018 | 25 | 2018 |
| Metakv: A key-value store for metadata management of distributed burst buffers T Wang, A Moody, Y Zhu, K Mohror, K Sato, T Islam, W Yu 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2017 | 23 | 2017 |
| Noise injection techniques to expose subtle and unintended message races K Sato, DH Ahn, I Laguna, GL Lee, M Schulz, CM Chambreau Proceedings of the 22Nd ACM SIGPLAN Symposium on Principles and Practice of …, 2017 | 22 | 2017 |
| Model compression and privacy preserving framework for federated learning X Zhu, J Wang, W Chen, K Sato Future Generation Computer Systems 140, 376-389, 2023 | 12 | 2023 |
| Record-and-replay techniques for HPC systems: A survey D Chapp, K Sato, DH Ahn, M Taufer Supercomputing Frontiers and Innovations 5 (1), 11-30, 2018 | 12 | 2018 |
| Burstfs: A distributed burst buffer file system for scientific applications T Wang, W Yu, K Sato, A Moody, K Mohror Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2016 | 11 | 2016 |
| Optimizing asynchronous multi-level checkpoint/restart configurations with machine learning T Dey, K Sato, B Nicolae, J Guo, J Domke, W Yu, F Cappello, K Mohror 2020 IEEE International Parallel and Distributed Processing Symposium …, 2020 | 10 | 2020 |
Satoshi MatsuokaRIKEN Center for Computational Science (R-CCS) / Tokyo Institute of Technology在 acm.org 的电子邮件经过验证
