The High Performance Conjugate Gradients Benchmark (HPCG benchmark) is a supercomputing benchmark test proposed by Michael Heroux from Sandia National Laboratories, and Jack Dongarra and Piotr Luszczek from the University of Tennessee.
[1][2] 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.
[3] Because it is internally I/O bound (the data for the benchmark resides in main memory as it is too large for processor caches), HPCG testing generally achieves only a tiny fraction of the peak FLOPS the computer could theoretically deliver.
[6] As of June 2018, the Summit supercomputer held the top spot in the HPCG performance rankings, followed by the Sierra and the K computer.
[7] In June of 2020, Summit was superseded by Fugaku with a speed of 16.0 HPCG-petaflops (an increase of 540%).