Evaluating GPGPU Memory Performance Through the C-AMAT Model
Authors: N. Zhang, C. Jiang, X.-H. Sun, S. Song
Date: November, 2017
Venue: The ACM SIGHPC 1st International Workshop on Memory Centric Programming for HPC (MCHPC 2017), in conjunction with SC'17, Denver, CO. USA2017. pp. 35-39
Type: Workshop
Abstract
General Purpose Graphics Processing Units (GPGPU) have become a popular platform to accelerate high performance applications. Although they provide exceptional computing power, GPGPU impose significant pressure on the off-chip memory system. Evaluating, understanding, and improving GPGPU data access delay has become an important research topic in high-performance computing. In this study, we utilize the newly proposed GPGPU/C-AMAT (Concurrent Average Memory Access Time) model to quantitatively evaluate GPGPU memory performance. Specifically, we extend the current C-AMAT model to include a GPGPU-specific modeling component and then provide its evaluation results.