对比技术和多用户商业工作负载的特征和缓存性能

ASPLOS VI Pub Date : 1994-11-01 DOI:10.1145/195473.195524
A.M.G. Maynard, Colette M. Donnelly, B. Olszewski
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引用次数: 226

摘要

经验表明,许多广泛使用的基准测试不能很好地预测运行商业应用程序的系统的性能。长期以来,由于缺乏代表性多用户商业工作负载的地址跟踪,对这种异常的研究一直受到阻碍。本文介绍了使用行业标准商业基准的跟踪进行的研究,该研究检查了技术和商业工作负载之间的特征差异,并说明了这些差异如何影响缓存性能。商业环境和技术环境在各自的分支行为、操作系统活动、I/O和调度特征方面有所不同。研究了各种单处理机指令和数据缓存的几何形状。商业工作负载的指令缓存结果表明,指令缓存性能不能再被忽视,因为这些工作负载具有比技术应用程序大得多的代码工作集。对于数据库工作负载,对内核和用户行为的分解表明,应用程序组件可能表现出与操作系统相似的行为,因此,可能会经历同样高的缺失率。本文还指出,在设计二级缓存时,必须考虑“调度”或进程切换特性。数据表明,提高二级缓存的关联性可以显著降低缺失率。总的来说,这项研究的结果应该有助于系统设计者选择一个在商业市场上表现良好的缓存配置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contrasting characteristics and cache performance of technical and multi-user commercial workloads
Experience has shown that many widely used benchmarks are poor predictors of the performance of systems running commercial applications. Research into this anomaly has long been hampered by a lack of address traces from representative multi-user commercial workloads. This paper presents research, using traces of industry-standard commercial benchmarks, which examines the characteristic differences between technical and commercial workloads and illustrates how those differences affect cache performance. Commercial and technical environments differ in their respective branch behavior, operating system activity, I/O, and dispatching characteristics. A wide range of uniprocessor instruction and data cache geometries were studied. The instruction cache results for commercial workloads demonstrate that instruction cache performance can no longer be neglected because these workloads have much larger code working sets than technical applications. For database workloads, a breakdown of kernel and user behavior reveals that the application component can exhibit behavior similar to the operating system and therefore, can experience miss rates equally high. This paper also indicates that “dispatching” or process switching characteristics must be considered when designing level-two caches. The data presented shows that increasing the associativity of second-level caches can reduce miss rates significantly. Overall, the results of this research should help system designers choose a cache configuration that will perform well in commercial markets.
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