Multi-GPU implementation of the NICAM atmospheric model

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Abstract

Climate simulation models are used for a variety of scientific problems and accuracy of the climate prognoses is mostly limited by the resolution of the models. Finer resolution results in more accurate prognoses but, at the same time, significantly increases computational complexity. This explains the increasing interest to the High Performance Computing (HPC), and GPU computations in particular, for the climate simulations. We present an efficient implementation of the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) on the multi-GPU environment. We have obtained performance results for the number of GPUs up to 320. These results were compared with the parallel CPU version and demonstrate that our GPU implementation gives 3 times higher performance over parallel CPU version. We have also developed and validated the performance model for a full-GPU implementation of the NICAM. Results show 4.5x potential acceleration over parallel CPU version. We believe that our results are general, in that in similar applications we could achieve similar speedups, and have the ability to predict its degree over CPUs. © 2013 Springer-Verlag.

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APA

Demeshko, I., Maruyama, N., Tomita, H., & Matsuoka, S. (2013). Multi-GPU implementation of the NICAM atmospheric model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7640 LNCS, pp. 175–184). https://doi.org/10.1007/978-3-642-36949-0_20

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