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Proceedings Paper

GPU-parallel performance of the community radiative transfer model (CRTM) with the optical depth in absorber space (ODAS)-based transmittance algorithm
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Paper Abstract

An Atmospheric radiative transfer model calculates radiative transfer of electromagnetic radiation through earth’s atmosphere. The Community Radiative Transfer Model (CRTM) is a fast model for simulating the infrared (IR) and microwave (MW) radiances of a given state of the Earth's atmosphere and its surface. The CRTM radiances have been used for satellite data assimilation in numerical weather prediction. The CRTM takes into account the radiance emission and absorption of various atmospheric gaseous as well as the emission and the reflection of various surface types. Two different transmittance algorithms are currently available in the CRTM OPTRAN: Optical Depth in Absorber Space (ODAS) and Optical Depth in Pressure Space (ODPS). ODAS in the current CRTM allows two variable absorbers (water vapor and ozone). In this paper, we examine the feasibility of using graphics processing units (GPUs) to accelerate the CRTM with the ODAS transmittance model. Using commodity GPUs for accelerating CRTM means that the hardware cost of adding high performance accelerators to computation hardware configuration are significantly reduced. Our results show that GPUs can provide significant speedup over conventional processors for the 8461-channel IASI sounder. In particular, a GPU on the dual-GPU NVIDIA GTX 590 card can provide a speedup 339x for the single-precision version of the CRTM ODAS compared to its single-threaded Fortran counterpart running on Intel i7 920 CPU.

Paper Details

Date Published: 8 November 2012
PDF: 9 pages
Proc. SPIE 8539, High-Performance Computing in Remote Sensing II, 853903 (8 November 2012); doi: 10.1117/12.979077
Show Author Affiliations
Jarno Mielikainen, Univ. of Wisconsin-Madison (United States)
Bormin Huang, Univ. of Wisconsin-Madison (United States)
Hung-Lung Allen Huang, Univ. of Wisconsin-Madison (United States)
Tsengdar Lee, NASA Headquarters (United States)


Published in SPIE Proceedings Vol. 8539:
High-Performance Computing in Remote Sensing II
Bormin Huang; Antonio J. Plaza, Editor(s)

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