Improvement and Optimization on Radar Extrapolation Algorithm Based on OpenCL

doi:10.3969/j.issn.1006-2475.2014.08.018

Abstract

Abstract:

Extrapolation based on radar data is one of the important methods for weather nowcasting. With the

increasing scale of the national weather radar network construction, and the enhancing about the refinement of

meteorological observational data, the extrapolation forecast based on regional and even national radar puzzle,

the computation time is very long. The time waiting for extrapolation computation usually lags behind the data’s

observation frequency which is once every six minutes. To solve the problem that the traditional extrapolation

algorithm is of high computational complexity and poor real-time, this paper discusses the heterogeneous computing

model based on GPU, and presents a parallel algorithm with OpenCL to achieve high performance, then analyzes the

bottlenecks of this application, and discusses how to bring up the computation speed by algorithm process

improvement and test data comparison. Some methods such as optimizing the mapping relationship of memory and

threads, utilizing local memory as high speed cache, and hiding CPU execution time, not only bring the efficiency

of the algorithm significantly improved, but also provide a reference for other optimization based on OpenCL

heterogeneous computing. Using AMD Graphic Core Next and Northern Islands which are two generation GPU

architectures as test platforms, and using Intel CPU parallel computing as a test reference, the test results show

that the improved algorithm consuming the same power dissipation under different hardware, the computing

performance is improved 15-22 times.

Key words: radar extrapolation algorithm, OpenCL, parallel computing, heterogeneous computing, GPU

CLC Number:

TP301.6

WANG Xing1, MIAO Chun-sheng1, WANG Xiu-jun2, FAN Zhong-xin1. Improvement and Optimization on Radar Extrapolation Algorithm Based on OpenCL[J]. Computer and Modernization, 2014, 0(8): 81-86+90.

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