Presenter

Biography
Kento Sato is the team leader of High Performance Big Data Research Team at RIKEN Center for Computational Science. His research area is distributed systems and parallel computing, particularly in High Performance Computing (HPC). Major focuses of his research are
application reproducibility (MPI reproducibility, and Validation), scalable fault tolerance (Scalable
checkpoint/restart, Fault tolerant MPI, Resilient system design), and I/O optimization (NVRAM,
Burst buffer, and Big data), co-designing and cloud computing. He received his Ph.D. in the Dept.
of Mathematical & Computing Sciences at Tokyo Tech in 2014, his M.S. in the Dept. of Mathematical & Computing Sciences at Tokyo Tech in 2010, and his B.S. in the Dept. of Information Science at Tokyo Tech in 2008.
application reproducibility (MPI reproducibility, and Validation), scalable fault tolerance (Scalable
checkpoint/restart, Fault tolerant MPI, Resilient system design), and I/O optimization (NVRAM,
Burst buffer, and Big data), co-designing and cloud computing. He received his Ph.D. in the Dept.
of Mathematical & Computing Sciences at Tokyo Tech in 2014, his M.S. in the Dept. of Mathematical & Computing Sciences at Tokyo Tech in 2010, and his B.S. in the Dept. of Information Science at Tokyo Tech in 2008.
Presentations
Posters
Research Posters
Poster 145: Improving Data Compression with Deep Predictive Neural Network for Time Evolutional Data
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Posters
Research Posters
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