OMPRacer: A Scalable and Precise Static Race Detector for OpenMP Programs

Bradley Swain, Yanze Li, Peiming Liu, I. Laguna, G. Georgakoudis, Jeff Huang
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引用次数: 12

Abstract

We present OMPRACER, a static tool that uses flow-sensitive, interprocedural analysis to detect data races in OpenMP programs. OMPRACER is fast, scalable, has high code coverage, and supports the most common OpenMP features by combining state-of-the-art pointer analysis, novel value-flow analysis, happens-before tracking, and generalized modelling of OpenMP APIs. Unlike dynamic tools that currently dominate data race detection, OMPRACER achieves almost 100% code coverage using static analysis to detect a broader category of races without running the program or relying on specific input or runtime behaviour. OMPRACER has competitive precision with dynamic tools like Archer and ROMP: passing 105/116 cases in DataRaceBench with a total accuracy of 91%. OMPRACER has been used to analyze several Exascale Computing Project proxy applications containing over 2 million lines of code in under 10 minutes. OMPRACER has revealed previously unknown races in an ECP proxy app and a production simulation for COVID19.
OMPRacer:一个可扩展的和精确的静态竞赛检测器的OpenMP程序
我们提出了OMPRACER,一个静态工具,使用流量敏感,程序间分析来检测OpenMP程序中的数据竞争。OMPRACER快速、可扩展、具有高代码覆盖率,并通过结合最先进的指针分析、新颖的价值流分析、发生前跟踪和OpenMP api的通用建模来支持最常见的OpenMP特性。与目前主导数据竞争检测的动态工具不同,OMPRACER使用静态分析实现了几乎100%的代码覆盖率,以检测更广泛的竞争类别,而无需运行程序或依赖特定的输入或运行时行为。与Archer和ROMP等动态工具相比,OMPRACER具有竞争力的精度:在DataRaceBench中通过105/116例,总精度为91%。OMPRACER已被用于在10分钟内分析包含超过200万行代码的几个Exascale Computing Project代理应用程序。OMPRACER在ECP代理应用程序和covid - 19生产模拟中揭示了以前未知的种族。
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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