会議発表論文 Co-locating Graph Analytics and HPC Applications

BROWN, KEVIN  ,  Brown, Kevin  ,  松岡, 聡  ,  MATSUOKA, SATOSHI

内容記述
We evaluate the on-node interference caused when co-locating traditional high-performance computing applications with a big-data application. Using kernel benchmarks from the NPB suite and a state-of-art graph analytics code, we explore different process placements and effects they have on application performance. Our results show that the most memory intensive HPC application (MG) experienced the highest performance variation during co-location.

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