Accelerating Geospatial Applications on Hybrid Architectures

Provided by: Institute of Electrical & Electronic Engineers
Topic: Hardware
Format: PDF
Accelerators have become critical in the process to develop supercomputers with exascale computing capability. In this paper, the authors examine the potential of two latest acceleration technologies, Nvidia K20 Kepler GPU and Intel Many Integrated Core (MIC) Architecture, for accelerating geospatial applications. They first apply a set of benchmarks under 3 different configurations, i.e., MPI+CPU, MPI+GPU, and MPI+MIC. This set of benchmarks includes embarrassingly parallel application, loosely communicating application, and intensely communicating application. It is found that the straightforward MPI implementation on MIC cores can achieve the same amount of performance speedup as hybrid MPI+GPU implementation when the same number of processors is used.

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