Portable exploitation of parallel and heterogeneous HPC architectures in neural simulation using SkePU

The complexity of modern HPC systems requires the use of new tools that support advanced programming models and offer portability and programmability of parallel and heterogeneous architectures. In this work we evaluate the use of SkePU framework in an HPC application from the neural computing domain. We demonstrate the successful deployment of the application based on SkePU using multiple back-ends (OpenMP, OpenCL and MPI) and present lessons-learned towards future extensions of the SkePU framework.

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