OpenCL Performance on the Intel Heterogeneous Architecture Research Platform

Steven Harris, R. Chamberlain, Christopher D. Gill
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引用次数: 4

Abstract

The fundamental operation of matrix multiplication is ubiquitous across a myriad of disciplines. Yet, the identification of new optimizations for matrix multiplication remains relevant for emerging hardware architectures and heterogeneous systems. Frameworks such as OpenCL enable computation orchestration on existing systems, and its availability using the Intel High Level Synthesis compiler allows users to architect new designs for reconfigurable hardware using C/C++. Using the HARPv2 as a vehicle for exploration, we investigate the utility of several traditional matrix multiplication optimizations to better understand the performance portability of OpenCL and the implications for such optimizations on cache coherent heterogeneous architectures. Our results give targeted insights into the applicability of best practices that were designed for existing architectures when used on emerging heterogeneous systems.
Intel异构架构研究平台上的OpenCL性能
矩阵乘法的基本运算在众多学科中无处不在。然而,确定矩阵乘法的新优化仍然与新兴的硬件体系结构和异构系统相关。像OpenCL这样的框架可以在现有系统上进行计算编排,并且它的可用性使用英特尔高级综合编译器允许用户使用C/ c++为可重构硬件构建新的设计。使用HARPv2作为探索的工具,我们研究了几种传统矩阵乘法优化的效用,以更好地理解OpenCL的性能可移植性以及这种优化对缓存一致异构架构的影响。我们的结果提供了针对在新兴异构系统上使用为现有架构设计的最佳实践的适用性的有针对性的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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