Performance evaluation and comparison of parallel conjugate gradient on modern multi-core accelerator and massively parallel systems

Abstract

Two parallel computer paradigms available today are multi-core accelerators such as the Sony, Toshiba and IBM Cell or Graphics Processing Unit (GPUs), and massively parallel message-passing machines such as the IBM Blue Gene (BG). The solution of systems of linear equations is one of the most central processing unit-intensive steps in engineering and simulation applications and can greatly benefit from the multitude of processing cores and vectorisation on today's parallel computers. We parallelise the conjugate gradient (CG) linear equation solver on the Cell Broadband Engine and the IBM Blue Gene/L machine. We perform a scalability analysis of CG on both machines across 1, 8 and 16 synergistic processing elements and 1–32 cores on BG with heptadiagonal matrices. The results indicate that the multi-core Cell system outperforms by three to four times the massively parallel BG system due to the Cell's higher communication bandwidth and accelerated vector processing capability.