Interferences between Communications and Computations in Distributed HPC Systems

International audienceParallel runtime systems such as MPI or task-based libraries provide models to manage both computation and communication by allocating cores, scheduling threads, executing communication algorithms. Efficiently implementing such models is challenging due to their interplay within the runtime system. In this paper, we assess interferences between communications and computations when they run side by side. We study the impact of communications on computations, and conversely the impact of computations on communication performance. We consider two aspects: CPU frequency, and memory contention. We have designed benchmarks to measure these phenomena. We show that CPU frequency variations caused by computation have a small impact on communication latency and bandwidth. However, we have observed on Intel, AMD and ARM processors, that memory contention may cause a severe slowdown of computation and communication when they occur at the same time. We have designed a benchmark with a tunable arithmetic intensity that shows how interferences between communication and computation actually depend on memory pressure of the application. Finally we have observed up to 90 % performance loss on communications with common HPC kernels such as CG and GEMM