2024/11/21 by Utpal Bora, Saurabh Joshi, Bora, Utpal +5 · 1 citation
Computer Science · Decision Sciences · #Advanced Data Storage Technologies #Computer science #Distributed #FOS: Computer and information sciences #Operating system #Parallel #Parallel computing #Programming language #Scientific Computing and Data Management #Software Engineering (cs.SE) #Software System Performance and Reliability #Software engineering #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2411.14590
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2024/11/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we present a technique for repairing data race errors in parallel programs written in C/C++ and Fortran using the OpenMP API. Our technique can also remove barriers that are deemed unnecessary for correctness. We implement these ideas in our tool called LLOR, which takes a language-independent approach to provide appropriate placements of synchronization constructs to avoid data races. To the best of our knowledge, LLOR is the only tool that can repair parallel programs that use the OpenMP API. We showcase the capabilities of LLOR by performing extensive experiments on 415 parallel programs.