Performance of runtime optimization on BLAST

A. Das, Jiwei Lu, Howard Chen, Jinpyo Kim, P. Yew, W. Hsu, Dong-yuan Chen
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引用次数: 11

Abstract

Optimization of a real world application BLAST is used to demonstrate the limitations of static and profile-guided optimizations and to highlight the potential of runtime optimization systems. We analyze the performance profile of this application to determine performance bottlenecks and evaluate the effect of aggressive compiler optimizations on BLAST. We find that applying common optimizations (e.g. O3) can degrade performance. Profile guided optimizations do not show much improvement across the board, as current implementations do not address critical performance bottlenecks in BLAST. In some cases, these optimizations lower performance significantly due to unexpected secondary effects of aggressive optimizations. We also apply runtime optimization to BLAST using the ADORE framework. ADORE is able to detect performance bottlenecks and deploy optimizations resulting in performance gains up to 58% on some queries using data cache prefetching.
BLAST运行时优化性能
BLAST用于演示静态优化和配置文件引导优化的局限性,并突出运行时优化系统的潜力。我们分析了该应用程序的性能概况,以确定性能瓶颈,并评估积极的编译器优化对BLAST的影响。我们发现应用常见的优化(例如O3)会降低性能。概要文件引导的优化并没有显示出全面的改进,因为当前的实现没有解决BLAST中的关键性能瓶颈。在某些情况下,由于主动优化的意外次要影响,这些优化会显著降低性能。我们还使用ADORE框架对BLAST进行了运行时优化。ADORE能够检测性能瓶颈并部署优化,从而在使用数据缓存预取的某些查询上获得高达58%的性能提升。
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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