High-Performance Conjugate Gradient (HPCG) Benchmark Task
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A High-Performance Conjugate Gradient (HPCG) Benchmark Task is a supercomputing benchmark task that ...
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- Counter-Example(s):
- See: Benchmark (Computing), Sparse Matrix Operation.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/HPCG_benchmark Retrieved:2017-11-13.
- The HPCG (high performance conjugate gradient) benchmark is a supercomputing benchmark test proposed by Jack Dongarra of the University of Tennessee, with Piotr Luszczek and Michael Heroux. It is intended to model the data access patterns of real-world applications such as sparse matrix calculations, thus testing the effect of limitations of the memory subsystem and internal interconnect of the supercomputer on its computing performance. Because it is internally I/O bound, HPCG testing generally achieves only a tiny fraction of the peak FLOPS of the computer. HPCG is intended to complement benchmarks such as the LINPACK benchmarks that put relatively little stress on the internal interconnect. The source of the HPCG benchmark is available on GitHub., the K computer supercomputer held the top spot in the HPCG performance rankings, followed by the Tianhe-2 and the Sunway TaihuLight.