Development of the GPU-based Stony-Brook University 5-class microphysics scheme in the weather research and forecasting model

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

doi:10.1117/12.901829

12 October 2011 Development of the GPU-based Stony-Brook University 5-class microphysics scheme in the weather research and forecasting model

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

Author Affiliations +

Proceedings Volume 8183, High-Performance Computing in Remote Sensing; 81830V (2011) https://doi.org/10.1117/12.901829
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

Abstract

The weather research and Forecasting (WRF) model in an atmospheric simulation system, which is designed for both operational and research use. This common tool aspect promotes closer ties between research and operational communities. It contains a lot a different physics and dynamics options reflecting the experience and input of the broad scientific community. The WRF physics categories and microphysics, cumulus parametrization, planetary boundary layer, land-surface model and radiation. Explicitly resolved water vapor, cloud and precipitation processes are included in microphysics. Several bulk water microphysics schemes are available within the Weather Research and Forecasting (WRF) model, with different numbers of simulated hydrometeor classes and methods for estimating their size fall speeds, distributions and densities. Stony-Brook University (SBU-YLIN) microphysics scheme is a 5-class scheme with riming intensity predicted to account for mixed-phase processes. In this paper, we develop an efficient graphics processing unit (GPU) based SBU-YLIN scheme. WRF computation domain is 3D grid layed over the earth. SBU-YLIN performs the same computation for each spatial position in the whole domain. This repletion of the same computation on different data sets allows using GPU's Single Instruction Multiple Dataset (SIMD) architecture. The GPU-based SBUYLIN scheme will be compared to a CPU-based single-threaded counterpart. The implementation achieves 213x speedup with I/O compared to a Fortran implementation running on a CPU. Without I/O the speedup is 896x.

Citation Download Citation

Jarno Mielikainen, Bormin Huang, Allen H.-L. Huang, and Mitchell D. Goldberg "Development of the GPU-based Stony-Brook University 5-class microphysics scheme in the weather research and forecasting model", Proc. SPIE 8183, High-Performance Computing in Remote Sensing, 81830V (12 October 2011); https://doi.org/10.1117/12.901829

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Clouds

Atmospheric modeling

Computer simulations

Crystals

Manufacturing

Physics

Graphics processing units

Show All Keywords

Keywords/Phrases

Search In:

Publication Years