In the era of Exascale computing, writing efficient parallel programs is indispensable, and, at the same time, writing sound parallel programs is very difficult. Specifying parallelism with frameworks such as OpenMP is relatively easy, but data races in these programs are an important source of bugs. In this article, we propose LLOV, a fast, lightweight, language agnostic, and static data race checker for OpenMP programs based on the LLVM compiler framework. We compare LLOV with other state-of-the-art data race checkers on a variety of well-established benchmarks. We show that the precision, accuracy, and the F1 score of LLOV is comparable to other checkers while being orders of magnitude faster. To the best of our knowledge, LLOV is the only tool among the state-of-the-art data race checkers that can verify a C/C++ or FORTRAN program to be data race free.

中文翻译：

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洛夫

在 Exascale 计算时代，编写高效的并行程序是必不可少的，同时编写好的并行程序也非常困难。使用 OpenMP 等框架指定并行性相对容易，但这些程序中的数据竞争是错误的重要来源。在本文中，我们提出了 LLOV，这是一种快速、轻量级、与语言无关的静态数据竞争检查器，用于基于 LLVM 编译器框架的 OpenMP 程序。我们在各种成熟的基准上将 LLOV 与其他最先进的数据竞争检查器进行比较。我们表明，LLOV 的精度、准确度和 F1 分数与其他检查器相当，同时速度要快几个数量级。据我们所知，