ParTeCL: Parallel Testing Using OpenCL

Vanya Yaneva, Ajitha Rajan, Christophe Dubach

Research output: Chapter in Book/Report/Conference proceedingConference contribution


With the growing complexity of software, the number of test cases needed for effective validation is extremely large. Executing these large test suites is expensive and time consuming, putting an enormous pressure on the software development cycle. In previous work, we proposed using Graphics Processing Units (GPUs) to accelerate test execution by running test cases in parallel on the GPU threads. However, the complexity of GPU programming poses challenges to the usability and effectiveness of the proposed approach.
In this paper we present ParTeCL - a compiler-assisted framework to automatically generate GPU code from sequential programs and execute their tests in parallel on the GPU. We show feasibility and performance achieved when executing test suites for 9 programs from an industry standard benchmark suite on the GPU. ParTeCL achieves an average speedup of 16x when compared to a single CPU for these benchmarks.
Original languageEnglish
Title of host publicationProceedings of ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)
Number of pages4
ISBN (Print)978-1-4503-5076-1
Publication statusPublished - 14 Jul 2017
EventACM SIGSOFT International Symposium on Software Testing and Analysis - Santa Barbara, United States
Duration: 10 Jul 201714 Jul 2017


ConferenceACM SIGSOFT International Symposium on Software Testing and Analysis
Abbreviated titleISSTA 2017
Country/TerritoryUnited States
CitySanta Barbara
Internet address


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