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

Jarno Mielikainen; Bormin Huang; Hung-Lung Allen Huang; Tsengdar Lee

doi:10.1117/12.979077

8 November 2012 GPU-parallel performance of the community radiative transfer model (CRTM) with the optical depth in absorber space (ODAS)-based transmittance algorithm

Jarno Mielikainen, Bormin Huang, Hung-Lung Allen Huang, Tsengdar Lee

Author Affiliations +

Proceedings Volume 8539, High-Performance Computing in Remote Sensing II; 853903 (2012) https://doi.org/10.1117/12.979077
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

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.

Citation Download Citation

Jarno Mielikainen, Bormin Huang, Hung-Lung Allen Huang, and Tsengdar Lee "GPU-parallel performance of the community radiative transfer model (CRTM) with the optical depth in absorber space (ODAS)-based transmittance algorithm", Proc. SPIE 8539, High-Performance Computing in Remote Sensing II, 853903 (8 November 2012); https://doi.org/10.1117/12.979077

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KEYWORDS

Transmittance

Atmospheric modeling

Radiative transfer

Absorption

Earth's atmosphere

Atmospheric optics

Computer programming

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