
Proceedings Paper
Optimizing Weather and Research Forecast (WRF) Thompson cloud microphysics on Intel Many Integrated Core (MIC)Format | Member Price | Non-Member Price |
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Paper Abstract
The Thompson cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and
Forecasting (WRF) model. The scheme is very suitable for massively parallel computation as there are no interactions
among horizontal grid points. Compared to the earlier microphysics schemes, the Thompson scheme incorporates a large
number of improvements. Thus, we have optimized the speed of this important part of WRF. Intel Many Integrated Core
(MIC) ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code
at trillions of calculations per second using the familiar programming model. In this paper, we present our results of
optimizing the Thompson microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel
Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a
high performance on-die bidirectional interconnect. The coprocessor supports all important Intel development tools. Thus,
the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum
performance out of MICs will require using some novel optimization techniques. Those optimization techniques are
discusses in this paper. The results show that the optimization improved MIC performance by 3.4x. Furthermore, the
optimized MIC code is 7.0x faster than the optimized multi-threaded code on the four CPU cores of a single socket Intel
Xeon E5-2603 running at 1.8 GHz.
Paper Details
Date Published: 28 May 2014
PDF: 12 pages
Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 91240Q (28 May 2014); doi: 10.1117/12.2055038
Published in SPIE Proceedings Vol. 9124:
Satellite Data Compression, Communications, and Processing X
Bormin Huang; Chein-I Chang; José Fco. López, Editor(s)
PDF: 12 pages
Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 91240Q (28 May 2014); doi: 10.1117/12.2055038
Show Author Affiliations
Jarno Mielikainen, Univ. of Wisconsin-Madison (United States)
Bormin Huang, Univ. of Wisconsin-Madison (United States)
Bormin Huang, Univ. of Wisconsin-Madison (United States)
Allen Huang, Univ. of Wisconsin-Madison (United States)
Published in SPIE Proceedings Vol. 9124:
Satellite Data Compression, Communications, and Processing X
Bormin Huang; Chein-I Chang; José Fco. López, Editor(s)
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