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Abstract
SummaryThe high‐performance conjugate gradients (HPCG) and high‐performance geometric multi‐grid (HPGMG) benchmarks are alternatives to the traditional LINPACK benchmark (HPL) in measuring the performance of modern HPC platforms. We performed HPCG and HPGMG benchmark tests on a Cray XE6/XK7 hybrid supercomputer, Blue Waters at National Center for Supercomputing Applications (NCSA). The benchmarks were tested on CPU‐based and GPU‐enabled nodes separately, and then we analyzed characteristic parameters that affect their performance. Based on our analyses, we performed HPCG and HPGMG runs in multiple program, multiple data (MPMD) mode in Cray Linux Environment in order to measure their hybrid performance on both CPU‐based and GPU‐enabled nodes. We observed and analyzed several performance issues during those tests. Based on lessons learned from this study, we provide recommendations about how to optimize science applications on modern hybrid HPC platforms.
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