High-performance conjugate gradient benchmark: A comprehensive survey

Citations

WEB OF SCIENCE

0
Citations

SCOPUS

0

초록

This survey paper focuses on examining the optimization techniques and trends for the High-Performance Conjugate Gradient (HPCG) benchmark employed in the last 10 years. The HPCG benchmark was introduced to eliminate the limitations of the High-Performance Linpack (HPL) benchmark and reflect the realistic performance measure of modern supercomputer architectures. Our study evaluates HPCG optimizations performed by High-Performance Computing (HPC) researchers on diverse hardware architectures such as CPU, GPU, MIC, and FPGA, etc., with a focus on optimizing the reference HPCG benchmark code for data formats, parallelization strategies, and architecture-specific tuning. We reviewed the optimizations performed by the researchers and presented a comprehensive analysis of these optimizations. This work offers the first comprehensive review of HPCG optimizations, aiming to discuss the previous findings and provide a systematic analysis for further optimizations in the future. Our study aims to guide researchers in identifying the most suitable directions to expand their knowledge and develop further optimization strategies in the HPCG benchmark.

키워드

High-performance conjugate gradient (HPCG)sparse linear systemsparallel computingiterative methodsHPCGSOLVERICCG
제목
High-performance conjugate gradient benchmark: A comprehensive survey
저자
Rizwan, MuhammadKim, ImbunmChoi, Jaeyoung
DOI
10.1177/10943420251393314
발행일
2026-05
유형
Article
저널명
International Journal of High Performance Computing Applications
40
3
페이지
291 ~ 321