Prof. Katsuki Fujisawa
Title： Advanced Computing & Optimization Infrastructure for Extremely Large-Scale Graphs on Post Peta-Scale Supercomputers
Speaker: Prof. Katsuki Fujisawa (Kyushu University, Japan & Advanced Industrial Science and Technology, Japan)
In this talk, we present our ongoing research project. The objective of this project is to develop advanced computing and optimization infrastructures for extremely large-scale graphs on post peta-scale supercomputers. We explain our challenge to Graph 500 benchmarks that are designed to measure the performance of a computer system for applications that require irregular memory and network access patterns. In 2014 to 2016, our project team was a winner of the 8th and 10th to 13th Graph500 benchmark.
We have started the research project for developing the Urban OS (Operating System) on a large-scale city from 2013. The Urban OS, which is regarded as one of emerging applications of cyber-physical system (CPS), gathers big data sets of people and transportation movements by utilizing different sensor technologies and storing them to the cloud storage system. The Urban OS employs the graph analysis system developed by our research project above and provides a feedback to a predicting and controlling center to optimize many social systems and services. We briefly explain our ongoing research project for realizing the Urban OS.
Professor Katsuki Fujisawa has been a Full Professor at the Institute of Mathematics for Industry (IMI) of Kyushu University. He had also been a research director of the JST (Japan Science and Technology Agency) CREST (Core Research for Evolutional Science and Technology) post-Peta High Performance Computing from 2011 to 2017. He received his Ph. D. from the Tokyo Institute of Technology in 1998. The objective of the JST CREST project is to develop an advanced computing and optimization infrastructure for extremely large-scale graphs on post peta-scale supercomputers. His project team has challenged the Graph500 benchmark, which is designed to measure the performance of a computer system for applications that require irregular memory and network access patterns. In 2014 to 2016, his project team was a winner of the 8th and 10th to 13th Graph500 benchmark. In 2017, He received the Prize for Science and Technology (Research Category), Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology, Japan.