使用OpenCL实现跨加速器、协处理器和多核处理器的面向吞吐量的高性能计算工作负载的性能和可移植性

Chongxiao Cao, M. Gates, A. Haidar, P. Luszczek, S. Tomov, I. Yamazaki, J. Dongarra
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引用次数: 13

摘要

自从加速器和协处理器成为面向吞吐量的HPC工作负载的主流硬件以来,已经提出了各种编程技术来提高性能和易用性方面的生产力。我们在许多硬件平台上对与广泛的科学应用相关的密集线性代数操作的重要子集的OpenCL的这些方面进行了评估。我们的研究结果表明,OpenCL的可移植性自我们之前的出版物以来已经得到了改善,并且许多新的和令人惊讶的使用场景可能与cpu上几十年的软件开发相媲美。综合的性能可移植性指标(尽管OpenCL标准没有承诺)反映了在移植过程中对性能关键操作进行调优的需求,并且我们展示了如果调优没有正确完成,将如何损失大部分可用效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance and Portability with OpenCL for Throughput-Oriented HPC Workloads across Accelerators, Coprocessors, and Multicore Processors
Ever since accelerators and coprocessors became the mainstream hardware for throughput-oriented HPC workloads, various programming techniques have been proposed to increase productivity in terms of both the performance and ease-of-use. We evaluate these aspects of OpenCL on a number of hardware platforms for an important subset of dense linear algebra operations that are relevant to a wide range of scientific applications. Our findings indicate that OpenCL portability has improved since our previous publication and many new and surprising usage scenarios are possible that rival those available after decades of software development on the CPUs. The combined performance-portability metric, even though not promised by the OpenCL standard, reflects the need for tuning performance-critical operations during the porting process and we show how a large portion of the available efficiency is lost if the tuning is not done correctly.
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