FADE: A programmable filtering accelerator for instruction-grain monitoring
FADE: A programmable filtering accelerator for instruction-grain monitoring
复制标题
FADE：用于指令粒度监控的可编程过滤加速器
DOI：
10.1109/hpca.2014.6835922
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Boris Grot
中科院分区：
文献类型：
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作者：
Sotiria Fytraki;Evangelos Vlachos;Yusuf Onur Koçberber;B. Falsafi;Boris Grot
指令粒度监控是一种强大的方法，可以支持广泛的错误查找工具。由于现有的软件方法会产生令人望而却步的运行时开销，研究人员已经将重点放在硬件支持的并行粒度监控。在最近的工作中反复出现的主题是使用硬件辅助过滤，以消除昂贵的软件分析。这项工作概括和扩展到一个可编程的过滤加速器提供巨大的灵活性和高速事件过滤以前的点解决方案。加速器的流水线微体系结构提供了每个周期一个应用程序事件的峰值过滤速率，这足以跟上运行被监视应用程序的积极的OoO核心。所提出的设计的一个独特的功能是能够动态地解决不可过滤的事件和后续事件之间的依赖关系，消除数据相关的失速和最大限度地提高加速器的性能。我们的评估结果显示，在各种监控工具中，监控速度仅为1.2- 1.8倍。
Instruction-grain monitoring is a powerful approach that enables a wide spectrum of bug-finding tools. As existing software approaches incur prohibitive runtime overhead, researchers have focused on hardware support for instruction-grain monitoring. A recurring theme in recent work is the use of hardware-assisted filtering so as to elide costly software analysis. This work generalizes and extends prior point solutions into a programmable filtering accelerator affording vast flexibility and at-speed event filtering. The pipelined microarchitecture of the accelerator affords a peak filtering rate of one application event per cycle, which suffices to keep up with an aggressive OoO core running the monitored application. A unique feature of the proposed design is the ability to dynamically resolve dependencies between unfilterable events and subsequent events, eliminating data-dependent stalls and maximizing accelerator's performance. Our evaluation results show a monitoring slowdown of just 1.2-1.8x across a diverse set of monitoring tools.