An Empirical Study of Parallelizing Test Execution Using CUDA Unified Memory and OpenMP GPU OffloadingNEXTA at Tamandaré

Authors: Taghreed Bagies and Ali Jannesari, Lowa State University, US. Abstract: The execution of software testing is costly and time-consuming. To accelerate the test execution, researchers have applied several methods to run the testing in parallel. One method of parallelizing the test execution is by using a GPU to distribute test case inputs among several threads running in parallel. In this paper, we investigate three programming models CUDA Unified Memory, CUDA Non-Unified Memory, and OpenMP GPU offloading to parallelize the test execution and discuss the challenges using these programing models. We use eleven benchmarks and parallelize their test suites by using these models. We evaluate their performance in terms of execution time, analyze the results, and report the limitations of using these programming models. Session Chair: Vahid Garousi