Browsing by Author Herbert, Kuchen
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Contemporary HPC hardware typically provides several levels of parallelism, e.g. multiple nodes, each having multiple cores (possibly with vectorization) and accelerators. Efficiently programming such systems usually requires skills in combining several low-level frameworks such as MPI, OpenMP, and CUDA. This overburdens programmers without substantial parallel programming skills. One way to overcome this problem and to abstract from details of parallel programming is to use algorithmic skeletons. In the present paper, we evaluate the multi-node, multi-CPU and multi-GPU implementation of the most essential skeletons Map, Reduce, and Zip. Our main contribution is a discussion of the ef... |
