LLOV: A Fast Static Data-Race Checker for OpenMP Programs
This addresses the difficulty of writing sound parallel programs for Exascale computing, though it is incremental as it builds on existing compiler frameworks.
The paper tackles the problem of detecting data races in OpenMP parallel programs by proposing LLOV, a fast static checker based on LLVM, which achieves comparable precision and F1 score to other state-of-the-art checkers while being orders of magnitude faster.
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 paper, 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.