WorkshopsMultigrid 2: Automatic Tuning of Parallel Multigrid Solvers with Hybrid Parallel Programming Models
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The multigrid method with OpenMP/MPI hybrid parallel programming model is expected to play an important role in large-scale scientific computing on post-peta/exa-scale supercomputer systems. Because the multigrid method includes various choices of parameters, selecting the optimum combination of these is a critical issue. In the present work, we focus on the selection of single-threading or multi-threading in the procedures of parallel multigrid solvers using OpenMP/MPI parallel hybrid programming models. We propose a simple empirical method for automatic tuning (AT) of related parameters. The performance of the proposed method is evaluated on the T2K Open Supercomputer (T2K/ Tokyo), the Cray XE6, and the Fujitsu FX10 using up to 8,192 cores. The proposed method for AT is effective, and the automatically tuned code provides twice the performance of the original one.
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Kengo Nakajima
2013-03-28
16:35:00 - 17:00:00
101 , Mathematics Research Center Building (ori. New Math. Bldg.)
The multigrid method with OpenMP/MPI hybrid parallel programming model is expected to play an important role in large-scale scientific computing on post-peta/exa-scale supercomputer systems. Because the multigrid method includes various choices of parameters, selecting the optimum combination of these is a critical issue. In the present work, we focus on the selection of single-threading or multi-threading in the procedures of parallel multigrid solvers using OpenMP/MPI parallel hybrid programming models. We propose a simple empirical method for automatic tuning (AT) of related parameters. The performance of the proposed method is evaluated on the T2K Open Supercomputer (T2K/ Tokyo), the Cray XE6, and the Fujitsu FX10 using up to 8,192 cores. The proposed method for AT is effective, and the automatically tuned code provides twice the performance of the original one.