OMPRacer:一个可扩展的和精确的静态竞赛检测器的OpenMP程序

SC20: International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2020-11-01 DOI:10.1109/SC41405.2020.00058

Bradley Swain, Yanze Li, Peiming Liu, I. Laguna, G. Georgakoudis, Jeff Huang

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引用次数: 12

摘要

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。

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

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.

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SC20: International Conference for High Performance Computing, Networking, Storage and Analysis

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