Scientific applications mainly rely on the MPI parallel programming model to reach high performance on supercomputers. The advent of manycore architectures (larger number of cores and lower amount of memory per core) leads to mix MPI with a threadbased model like OpenMP. But integrating two different programming models inside the same application can be tricky and generate complex bugs. Thus, the correctness of hybrid programs requires a special care regarding MPI calls location. For example,

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... entical MPI collective operations cannot be performed by multiple non-synchronized threads. To tackle this issue, this paper proposes a static analysis and a reduced dynamic instrumentation to detect bugs related to misuse of MPI collective operations inside or outside threaded regions. This work extends PARCOACH designed for MPI-only applications and keeps the compatibility with these algorithms. We validated our method on multiple hybrid benchmarks and applications with a low overhead.