一种时间不可知的SVE优化方法

M. T. Cruz, Daniel Ruiz, Roxana Rusitoru
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引用次数: 4

摘要

随着我们快速接近百亿亿级并向下一个挑战迈进,我们正在探索更广泛的技术和架构。考虑的时间范围越长,原型硬件可用的可能性就越小。探索新体系结构扩展的一种流行方法是在现有平台上模拟它们。Arm指令模拟器(ArmIE)就是这样一个工具,我们在现有的Armv8平台上使用它来运行Arm最新的矢量架构,可扩展矢量扩展(SVE)。为了帮助将应用程序移植到SVE,我们开发了一种基于ArmIE的应用程序优化方法,该方法使用与时间无关的度量来评估应用程序质量。我们展示了我们如何通过使用我们的方法成功地将高性能共轭梯度(HPCG)高性能计算基准优化到SVE,从而产生一个手动优化的基于本征的版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asvie: A Timing-Agnostic SVE Optimization Methodology
As we are quickly approaching exascale and moving onwards towards the next challenge, we are exploring a wider range of technologies and architectures. The further out the timeframes considered, the less likely prototype hardware is available. A popular method of exploring new architectural extensions is to emulate them on existing platforms. The Arm Instruction Emulator (ArmIE) is such a tool, which we use on existing Armv8 platforms to run Arm's latest vector architecture, the Scalable Vector Extension (SVE). To aid with porting applications towards SVE, we developed an application optimization methodology based on ArmIE that uses timing-agnostic metrics to assess application quality. We show how we have successfully optimized the High Performance Conjugate Gradient (HPCG) High Performance Computing benchmark to SVE by using our methodology, resulting in a hand-optimized intrinsics-based version.
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