Watching for Software Inefficiencies with Witch

Shasha Wen, Xu Liu, John L. Byrne, Milind Chabbi
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引用次数: 28

Abstract

Inefficiencies abound in complex, layered software. A variety of inefficiencies show up as wasteful memory operations. Many existing tools instrument every load and store instruction to monitor memory, which significantly slows execution and consumes enormously extra memory. Our lightweight framework, Witch, samples consecutive accesses to the same memory location by exploiting two ubiquitous hardware features: the performance monitoring units (PMU) and debug registers. Witch performs no instrumentation. Hence, witchcraft---tools built atop Witch---can detect a variety of software inefficiencies while introducing negligible slowdown and insignificant memory consumption and yet maintaining accuracy comparable to exhaustive instrumentation tools. Witch allowed us to scale our analysis to a large number of code bases. Guided by witchcraft, we detected several performance problems in important code bases; eliminating these inefficiencies resulted in significant speedups.
用Witch观察软件的低效率
在复杂、分层的软件中,效率低下比比皆是。各种低效率表现为浪费内存操作。许多现有的工具通过检测每个加载和存储指令来监控内存,这大大降低了执行速度,并消耗了大量额外的内存。我们的轻量级框架Witch通过利用两个普遍存在的硬件特性:性能监控单元(PMU)和调试寄存器,对对同一内存位置的连续访问进行采样。Witch不执行任何检测。因此,巫术——构建在Witch之上的工具——可以检测到各种软件的低效率,同时引入可忽略不计的减速和微不足道的内存消耗,同时保持与详尽的仪器工具相当的准确性。Witch允许我们将分析扩展到大量的代码库。在巫术的指导下,我们在重要的代码库中发现了几个性能问题;消除这些低效率带来了显著的速度提升。
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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