Paper
21 October 2014 Initial results on computational performance of Intel Many Integrated Core (MIC) architecture: implementation of the Weather and Research Forecasting (WRF) Purdue-Lin microphysics scheme
Author Affiliations +
Proceedings Volume 9247, High-Performance Computing in Remote Sensing IV; 92470C (2014) https://doi.org/10.1117/12.2068360
Event: SPIE Remote Sensing, 2014, Amsterdam, Netherlands
Abstract
Purdue-Lin scheme is a relatively sophisticated microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme includes six classes of hydro meteors: water vapor, cloud water, raid, cloud ice, snow and graupel. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. In this paper, we accelerate the Purdue Lin scheme using Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi is a high performance coprocessor consists of up to 61 cores. The Xeon Phi is connected to a CPU via the PCI Express (PICe) bus. In this paper, we will discuss in detail the code optimization issues encountered while tuning the Purdue-Lin microphysics Fortran code for Xeon Phi. In particularly, getting a good performance required utilizing multiple cores, the wide vector operations and make efficient use of memory. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 4.2x. Furthermore, the same optimizations improved performance on Intel Xeon E5-2603 CPU by a factor of 1.2x compared to the original code.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jarno Mielikainen, Bormin Huang, and Allen H.-L. Huang "Initial results on computational performance of Intel Many Integrated Core (MIC) architecture: implementation of the Weather and Research Forecasting (WRF) Purdue-Lin microphysics scheme", Proc. SPIE 9247, High-Performance Computing in Remote Sensing IV, 92470C (21 October 2014); https://doi.org/10.1117/12.2068360
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Cited by 3 scholarly publications.
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KEYWORDS
Clouds

Physics

Computer architecture

Computer programming

Atmospheric modeling

Parallel computing

Acoustics

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