SIGMA: A Simulator Infrastructure to Guide Memory Analysis

L. D. Rose, K. Ekanadham, J. Hollingsworth, S. Sbaraglia
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引用次数: 82

Abstract

In this paper we present SIGMA (Simulation Infrastructure to Guide Memory Analysis), a new data collection framework and family of cache analysis tools. The SIGMA environment provides detailed cache information by gathering memory reference data using software-based instrumentation. This infrastructure can facilitate quick probing into the factors that influence the performance of an application by highlighting bottleneck scenarios including: excessive cache/TLB misses and inefficient data layouts. The tool can also assist in perturbation analysis to determine performance variations caused by changes to architecture or program. Our validation tests using the SPEC Swim benchmark show that most of the performance metrics obtained with SIGMA are within 1% of the metrics obtained with hardware performance counters, with the advantage that SIGMA provides performance data on a data structure level, as specified by the programmer.
SIGMA:引导内存分析的模拟器基础结构
在本文中,我们提出了SIGMA(模拟基础设施来指导内存分析),一个新的数据收集框架和缓存分析工具家族。SIGMA环境通过使用基于软件的工具收集内存参考数据来提供详细的缓存信息。这个基础设施可以通过突出瓶颈场景来促进快速探测影响应用程序性能的因素,这些瓶颈场景包括:过多的缓存/TLB丢失和低效的数据布局。该工具还可以帮助进行扰动分析,以确定由架构或程序更改引起的性能变化。我们使用SPEC Swim基准的验证测试表明,使用SIGMA获得的大多数性能指标都在使用硬件性能计数器获得的指标的1%以内,其优点是SIGMA在数据结构级别上提供性能数据,由程序员指定。
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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