Enabling Mixed OpenMP/MPI Programming on Hybrid CPU/GPU Computing Architecture

Hybrid CPU/GPU computing architecture recently has become an alternative platform for high performance computing. This architecture provides massive computational power with lower energy consumption and less economic cost than the traditional one using only CPUs. However, the complexity of the GPU programming is too high for users to move their applications toward this hybrid computing architecture. To resolve this problem, we propose a framework called OMPICUDA for users to develop parallel applications on the hybrid CPU/GPU clusters by mixing the APIs of OpenMP and MPI. Furthermore, this framework allows users to select GPUs or CPUs for the execution of different parallel regions in the same program according to the properties of the regions, and supports resource reallocation based on the states of CPUs and GPUs.