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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