MPISE: Symbolic Execution of MPI Programs
This addresses the issue of missed bugs in parallel computing for developers of MPI programs, representing an incremental improvement over existing methods.
The paper tackles the problem of bug detection in MPI programs by employing symbolic execution for input coverage and an on-the-fly schedule algorithm to reduce interleaving explorations for non-determinism coverage, resulting in effective and efficient bug detection as shown in experiments on benchmark and real-world programs.
Message Passing Interfaces (MPI) plays an important role in parallel computing. Many parallel applications are implemented as MPI programs. The existing methods of bug detection for MPI programs have the shortage of providing both input and non-determinism coverage, leading to missed bugs. In this paper, we employ symbolic execution to ensure the input coverage, and propose an on-the-fly schedule algorithm to reduce the interleaving explorations for non-determinism coverage, while ensuring the soundness and completeness. We have implemented our approach as a tool, called MPISE, which can automatically detect the deadlock and runtime bugs in MPI programs. The results of the experiments on benchmark programs and real world MPI programs indicate that MPISE finds bugs effectively and efficiently. In addition, our tool also provides diagnostic information and replay mechanism to help understanding bugs.