Pushing the Limits of the Maya Supercomputer with the HPCG Benchmark
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Slettebak, Jack. “Pushing the Limits of the Maya Supercomputer with the HPCG Benchmark.” UMBC Review: Journal of Undergraduate Research 17 (2016): 162–75. https://ur.umbc.edu/wp-content/uploads/sites/354/2016/05/slettebakJack.pdf
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Parallel architectures and algorithms sit at the forefront of high performance computing as ways to decrease the execution time of a computationally intense problem. Parallel architecture is hardware that has multiple cores or multiple threads, and a parallel algorithm is a software algorithm designed to be able to use multiple cores or threads simultaneously. The supercomputer maya in the UMBC High Performance Computing Facility (HPCF) is designed to provide a resource for the researchers of various disciplines who require a powerful parallel computer to solve the problems they encounter in their work. Using the newly developed High Performance Conjugate Gradient (HPCG) benchmark (www.hpcg-benchmark.org) from Sandia National Laboratories, this effort identified several runtime optimizations that allow for maximum performance on maya. These optimizations nearly doubled the reported performance of the benchmark from previous tests. A total throughput of 450 GFLOP/s was achieved using only a fourth of the hardware available on maya.