GPU Compute Unified Device Architecture (CUDA)-based Parallelization of the RRTMG Shortwave Rapid Radiative Transfer Model

Abstract

Radiative transfer of electromagnetic radiation through a planetary atmosphere is computed using an atmospheric radiative transfer model (RTM). One RTM is the rapid RTM (RRTM), which calculates both longwave and shortwave atmospheric radiative fluxes and heating rates. Broadband radiative transfer code for general circulation model (GCM) applications, rapid RTM for global (RRTMG), is based on the single-column reference code, RRTM. The focus of this paper is on the RRTMG shortwave (RRTMG_SW) model. Due to its accuracy, RRTMG_SW has been implemented operationally in many weather forecast and climate models. In this paper, we examine the feasibility of using graphics processing units (GPUs) to accelerate the RRTMG_SW for a massive amount of atmospheric profiles. In recent years, GPUs have emerged as a low-cost, low-power, and a very high-performance alternative to conventional central processing units (CPUs). GPUs can provide a substantial improvement in RRTMG speed by supporting the parallel computation of large numbers of independent radiative calculations in separate atmospheric profiles. A GPU-compatible version of RRTMG was implemented and thorough testing was performed to ensure that the original level of accuracy is retained. Our results show that GPUs can provide significant speedup over conventional CPUs. In particular, Nvidia’s Tesla K40 GPU card can provide a speedup of ${{202}} \times $ compared to its single-threaded Fortran counterpart running on Intel Xeon E5-2603 CPU, whereas the speedup for four CPU cores, on one CPU socket, with respect to 1 CPU core is ${{5}}.{{6}} \times $ .