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Content Provider | IEEE Xplore Digital Library |
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Author | Jun Wang Bormin Huang Huang, A. Goldberg, M.D. |
Copyright Year | 2011 |
Abstract | The Weather Research and Forecast (WRF) Double Moment 5-class (WDM5) mixed ice microphysics scheme predicts mixing ratio of hydrometeors and their number concentrations for warm rain species including clouds and rain. WDM5 can be computed in parallel in the horizontal domain using a many-core GPU. In order to obtain better GPU performance, we manually rewrote the original WDM5 Fortran module into a highly parallel CUDA C program. The GPU-based implementation of WDM5 microphysics scheme on 1 GTX590 GPU achieves a significant speedup of 147× over its CPU-based single-threaded counterpart when we use asynchronous data transfer and non-coalesced memory access. More importantly, the speedup excluding the host-device data transfer time is 206× when using coalesced memory access. Since the WDM5 microphysics scheme is only an intermediate module of the entire WRF model, 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. |
Starting Page | 1032 |
Ending Page | 1037 |
File Size | 253718 |
Page Count | 6 |
File Format | |
ISBN | 9781457718755 |
ISSN | 15219097 |
e-ISBN | 9780769545769 |
DOI | 10.1109/ICPADS.2011.160 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-12-07 |
Publisher Place | Taiwan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Graphics processing unit Wavelength division multiplexing Clouds Ice Snow Rain Instruction sets CUDA WRF WDM5 microphysics scheme GPU |
Content Type | Text |
Resource Type | Article |
Subject | Hardware and Architecture |
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