On the acceleration of Eta Ferrier Cloud Microphysics Scheme in the Weather Research and Forecasting (WRF) model using a GPU

Melin Huang; Jarno Mielikainen; Bormin Huang; H.-L. Allen Huang; Mitchell D. Goldberg

doi:10.1117/12.976908

8 November 2012 On the acceleration of Eta Ferrier Cloud Microphysics Scheme in the Weather Research and Forecasting (WRF) model using a GPU

Melin Huang, Jarno Mielikainen, Bormin Huang, H.-L. Allen Huang, Mitchell D. Goldberg

Author Affiliations +

Proceedings Volume 8539, High-Performance Computing in Remote Sensing II; 85390K (2012) https://doi.org/10.1117/12.976908
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

The Eta Ferrier cloud microphysics scheme is a sophisticated cloud microphysics module in the Weather Research and Forecasting (WRF) model. In this paper, we present the approach and the results of accelerating the Eta Ferrier microphysics scheme on NVIDIA Graphics Processing Units (GPUs). We discuss how our GPU implementation takes advantage of the parallelism in Eta Ferrier scheme, leading to a highly efficient GPU acceleration. We implement the Eta Ferrier microphysics scheme on NVidia GTX 590 GPU. Our 1-GPU implementation achieves an overall speedup of 37 as compared with a single thread CPU. Since Eta Ferrier microphysics scheme is only an intermediate module of the entire WRF model, the GPU I/O should not occur, i.e. its input data should be already available in the GPU global memory from previous modules and its output data should reside at the GPU global memory for later usage by other modules. The speedup without the host-device data transfer time is 272 with respect to its serial version running on 3.20GHz Intel® Core^TM i7 970 CPU.

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Melin Huang, Jarno Mielikainen, Bormin Huang, H.-L. Allen Huang, and Mitchell D. Goldberg "On the acceleration of Eta Ferrier Cloud Microphysics Scheme in the Weather Research and Forecasting (WRF) model using a GPU", Proc. SPIE 8539, High-Performance Computing in Remote Sensing II, 85390K (8 November 2012); https://doi.org/10.1117/12.976908

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