Abstract
The importance of high-performance computing is increasing, and Exascale systems will be feasible in a few years. These systems can be achieved by enhancing the hardware’s ability as well as the parallelism in the application by integrating more than one programming model. One of the dual-programming model combinations is Message Passing Interface (MPI) + OpenACC, which has several features including increased system parallelism, support for different platforms with more performance, better productivity, and less programming effort. Several testing tools target parallel applications built by using programming models, but more effort is needed, especially for high-level Graphics Processing Unit (GPU)-related programming models. Owing to the integration of different programming models, errors will be more frequent and unpredictable. Testing techniques are required to detect these errors, especially runtime errors resulting from the integration of MPI and OpenACC; studying their behavior is also important, especially some OpenACC runtime errors that cannot be detected by any compiler. In this paper, we enhance the capabilities of ACC_TEST to test the programs built by using the dual-programming models MPI + OpenACC and detect their related errors. Our tool integrated both static and dynamic testing techniques to create ACC_TEST and allowed us to benefit from the advantages of both techniques reducing overheads, enhancing system execution time, and covering a wide range of errors. Finally, ACC_TEST is a parallel testing tool that creates testing threads based on the number of application threads for detecting runtime errors.
Highlights
Exascale systems will be available in a few years
Parallel programs built by using programming models have been targeted by different testing tools
There is a shortage of testing tools targeting parallel systems, which use dual-programming models
Summary
Exascale systems will be available in a few years. These systems can be achieved by enhancing hardware ability as well as parallelism in the application by integrating different programming models using dual- and tri-programming models. Exascale systems can achieve 1018 floating-point operations. Parallel programs built by using programming models have been targeted by different testing tools. Because of the integration between different programming models, errors will be more frequent and unpredictable and need testing techniques to detect them. As a result, building a testing tool targeting parallel programs is not an easy task, especially when these parallel programs are built using integrated programming models. There is a shortage of testing tools targeting parallel systems, which use dual-programming models
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
