Linkage of XcalableMP and Python languages for high productivity on HPC cluster system: application to graph order/degree problem
作者： Masahiro Nakao , Hitoshi Murai , Taisuke Boku , Mitsuhisa Sato
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摘要: When developing applications on high-performance computing (HPC) cluster systems, Partitioned Global Address Space (PGAS) languages are used due to their high productivity and performance. However, in order more efficiently develop such applications, it is also important be able combine a PGAS language with other instead of using single alone. We have designed an XcalableMP (XMP) language, developed Omni Compiler as XMP compiler. In this paper, we report the development linkage functions between {C, Fortran, or Python} for Compiler. Furthermore, functional example interworking Python, discuss application Graph Order/degree problem. Specifically, paralleled all shortest paths among vertices searches XMP. results original Python were compared, found that performance was 21% faster than CPU core. Moreover, when applying HPC system 1,280 cores 64 compute nodes, could achieve 921 times better
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