LLOV: A Fast Static Data-Race Checker for OpenMP Programs
Utpal Bora, Santanu Das, Pankaj Kukreja, Saurabh Joshi, Ramakrishna, Upadrasta, Sanjay Rajopadhye

TL;DR
LLOV is a fast, static, language-agnostic data race checker for OpenMP programs that offers comparable accuracy to existing tools while significantly improving speed, and uniquely supports C/C++ and FORTRAN.
Contribution
LLOV introduces a novel static data race detection tool for OpenMP programs that is faster and supports multiple languages, including FORTRAN.
Findings
LLOV achieves comparable precision and F1 score to existing tools.
LLOV is orders of magnitude faster than other data race checkers.
LLOV uniquely verifies C/C++ and FORTRAN programs for data races.
Abstract
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.
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