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Terascale spectral element dynamical core for atmospheric general circulation models

Richard D. Loft, Stephen James Thomas, John M. Dennis

Open publisher page 70 citations

Abstract

Climate modeling is a grand challenge problem where scientific progress is measured not in terms of the largest problem that can be solved but by the highest achievable integration rate. These models have been notably absent in previous Gordon Bell competitions due to their inability to scale to large processor counts. A scalable and efficient spectral element atmospheric model is presented. A new semi-implicit time stepping scheme accelerates the integration rate relative to an explicit model by a factor of two, achieving 130 years per day at T63L30 equivalent resolution. Execution rates are reported for the standard shallow water and Held-Suarez climate benchmarks on IBM SP clusters. The explicit T170 equivalent multi-layer shallow water model sustains 343 Gflops at NERSC, 206 Gflops at NPACI (SDSC) and 127 Gflops at NCAR. An explicit Held-Suarez integration sustains 369 Gflops on 128 16-way IBM nodes at NERSC.

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What this paper is about

Climate modeling is a grand challenge problem where scientific progress is measured not in terms of the largest problem that can be solved but by the highest achievable integration rate. These models have been notably absent in previous Gordon Bell competitions due to their inability to scale to large processor counts. A scalable and efficient spectral element atmospheric model is presented. A new semi-implicit time stepping scheme accelerates the integration rate relative to an explicit model by a factor of two, achieving 130 years per day at T63L30 equivalent resolution. Execution rates are reported for the standard shallow water and Held-Suarez climate benchmarks on IBM SP clusters. The explicit T170 equivalent multi-layer shallow water model sustains 343 Gflops at NERSC, 206 Gflops at NPACI (SDSC) and 127 Gflops at NCAR. An explicit Held-Suarez integration sustains 369 Gflops on 128 16-way IBM nodes at NERSC.

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Available abstract

Climate modeling is a grand challenge problem where scientific progress is measured not in terms of the largest problem that can be solved but by the highest achievable integration rate. These models have been notably absent in previous Gordon Bell competitions due to their inability to scale to large processor counts. A scalable and efficient spectral element atmospheric model is presented. A new semi-implicit time stepping scheme accelerates the integration rate relative to an explicit model by a factor of two, achieving 130 years per day at T63L30 equivalent resolution. Execution rates are reported for the standard shallow water and Held-Suarez climate benchmarks on IBM SP clusters. The explicit T170 equivalent multi-layer shallow water model sustains 343 Gflops at NERSC, 206 Gflops at NPACI (SDSC) and 127 Gflops at NCAR. An explicit Held-Suarez integration sustains 369 Gflops on 128 16-way IBM nodes at NERSC.

Key concepts: FLOPS, Computer science, Scalability, IBM, Supercomputer, Parallel computing, Computational science, Atmospheric model

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