Abstract
Recently, building massively parallel systems has become increasingly important with coming improvements of Exascale related technologies. For building such systems, a combination of programming models is needed to increase the system's parallelism. One of these combinations is the dual-programming model (MPI+X) that has different structures to increase parallelism in heterogeneous systems that include CPUs and GPUs. (MPI + OpenACC) has many advantages and features that increase parallelism with respect to heterogeneous architecture and support different platforms with more performance, productivity and programmability. However, building parallel systems with different programming models is even harder and is more error-prone, which is not easy to test. Also, testing parallel applications is a difficult task, because parallel errors are hard to detect due to the non-determined behavior of the parallel application. Even after detecting the errors and modifying the source code, it is not easy to determine whether the errors have been corrected or remain hidden. Furthermore, integrating two different programming models inside the same application makes it even more difficult to test.
We proposed a parallel hybrid-testing tool for detecting run-time errors for systems implemented in C++ and (MPI + OpenACC). The hybrid techniques combine static and dynamic testing techniques for detecting real and potential run-time errors by analyzing the source code during run time. Using parallel hybrid techniques will enhance the testing time and cover a wide range of errors. Finally, to the best of our knowledge, identifying and classifying OpenACC errors has not been done before, and there is no parallel testing tool designed to test applications programmed by using the dual-programming model (MPI + OpenACC) or the single-programming models like OpenACC.