LibWater
Ivan Grasso, Simone Pellegrini, Biagio Cosenza, Thomas Fahringer · 2013
Clusters of heterogeneous nodes composed of multi-core CPUs and GPUs are increasingly being used for High Performance Computing (HPC) due to the benefits in peak performance and energy efficiency. In order to fully harvest the computational capabilities of such architectures, application developers often employ a combination of different parallel programming paradigms (e.g. OpenCL, CUDA, MPI and OpenMP), also known in literature as hybrid programming, which makes application development very challenging. Furthermore, these languages offer limited support to orchestrate data and computations for heterogeneous systems.