A Hybrid Approach for Large Cache Performance Studies

D. Daly, Parijat Dube, Kaoutar El Maghraoui, D. Poff, Li Zhang
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引用次数: 1

Abstract

Recent technology trends are leading to the possibility of computer systems having last level caches significantly larger than those that exist today. Traditionally, cache effectiveness has been modeled through trace-driven simulation tools, however, these tools are not up to the task of modeling very large caches. Because of the limited length of available traces, the tools cannot capture behavior across long enough periods of time to adequately simulate a very large cache. We present mprofiler, a tool that characterizes the memory access pattern of workloads, and present a novel hybrid modeling technique that models cache behavior across a much larger time scale than previously possible. Our methodology combines memory access patterns captured by different tools (e.g., mprofiler) at different time scales and develops analytical techniques that allow spanning the required time frame and predicting the performance of very large caches.
大型缓存性能研究的混合方法
最近的技术趋势正在导致计算机系统具有比现有的大得多的最后一级缓存的可能性。传统上,缓存有效性是通过跟踪驱动的仿真工具进行建模的,然而,这些工具无法完成对非常大的缓存进行建模的任务。由于可用跟踪的长度有限,这些工具无法在足够长的时间内捕获行为,以充分模拟非常大的缓存。我们介绍了mprofiler,一个描述工作负载内存访问模式的工具,并介绍了一种新的混合建模技术,该技术可以在比以前更大的时间尺度上对缓存行为进行建模。我们的方法结合了由不同工具(例如mprofiler)在不同时间尺度上捕获的内存访问模式,并开发了允许跨越所需时间框架并预测超大缓存性能的分析技术。
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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