The Alberta Workloads for the SPEC CPU 2017 Benchmark Suite

J. N. Amaral, E. Borin, Dylan R. Ashley, C. Benedicto, Elliot Colp, Joao Henrique Stange Hoffmam, Marcus Karpoff, Erick Ochoa, Morgan Redshaw, R. E. Rodrigues
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引用次数: 17

Abstract

A proper evaluation of techniques that require multiple training and evaluation executions of a benchmark, such as Feedback-Directed Optimization (FDO), requires multiple workloads that can be used to characterize variations on the behaviour of a program based on the workload. This paper aims to improve the performance evaluation of computer systems — including compilers, computer architecture simulation, and operating-system prototypes — that rely on the industrystandard SPEC CPU benchmark suite. A main concern with the use of this suite in research is that it is distributed with a very small number of workloads. This paper describes the process to create additional workloads for this suite and offers useful insights in many of its benchmarks. The set of additional workloads created, named the Alberta Workloads for the SPEC CPU 2017 Benchmark Suite1 is made freely available with the goal of providing additional data points for the exploration of learning in computing systems. These workloads should also contribute to ameliorate the hidden learning problem where a researcher sets parameters to a system during development based on a set of benchmarks and then evaluates the system using the very same set of benchmarks with the very same workloads.
SPEC CPU 2017基准测试套件的Alberta工作负载
对需要多次训练和执行基准评估的技术(如反馈导向优化(Feedback-Directed Optimization, FDO))进行适当的评估需要多个工作负载,这些工作负载可用于描述基于工作负载的程序行为的变化。本文旨在改进计算机系统的性能评估——包括编译器、计算机体系结构模拟和操作系统原型——这些系统都依赖于行业标准SPEC CPU基准套件。在研究中使用这个套件的一个主要问题是,它是分布在非常少的工作负载上的。本文描述了为该套件创建额外工作负载的过程,并在其许多基准测试中提供了有用的见解。创建的额外工作负载集,命名为SPEC CPU 2017基准套件的Alberta工作负载,是免费提供的,目的是为探索计算系统中的学习提供额外的数据点。这些工作负载还有助于改善隐藏的学习问题,即研究人员在开发过程中根据一组基准为系统设置参数,然后使用具有相同工作负载的相同基准集评估系统。
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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