基于C-AMAT模型的GPGPU内存性能评估

Ning Zhang, Chuntao Jiang, Xian-He Sun, S. Song
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引用次数: 6

摘要

通用图形处理单元(GPGPU)已经成为一个流行的加速高性能应用程序的平台。尽管GPGPU提供了卓越的计算能力,但对片外存储系统施加了巨大的压力。评估、理解和改进GPGPU的数据访问延迟已成为高性能计算领域的重要研究课题。在本研究中,我们利用新提出的GPGPU/C-AMAT(并发平均内存访问时间)模型来定量评估GPGPU内存性能。具体来说,我们扩展了现有的C-AMAT模型,加入了一个特定于gpgpu的建模组件,并提供了其评估结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating GPGPU Memory Performance Through the C-AMAT Model
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.
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