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Atmospheric radiative transfer models calculate radiative transfer of electromagnetic radiation through a planetary atmosphere. One of such models is the rapid radiative transfer model (RRTM), which evaluates longwave and shortwave atmospheric radiative fluxes and heating rates. The RRTM for general circulation models (GCMs), RRTMG, is an accelerated version based on the single-column reference of RRTM. The longwave radiation scheme of RRTM for GCMs (RRTMGLW) is one model that utilizes the correlated-k approach to calculate longwave fluxes and heating rates for application to GCMs. In this paper, the feasibility of using graphics processing units (GPUs) to accelerate the in weather research and forecasting (WRF) model is examined. GPUs allow a substantial performance improvement in RRTMGLW with a large number of parallel compute cores at low cost and power. Our GPU version of RRTMGLW yields the bit-exact outputs as its original Fortran code. Our results show that NVIDIA's K40 GPU achieves a speedup of x as compared to its CPU counterpart running on one CPU core of Intel Xeon E5-2603, whereas the speedup for one CPU socket (4 cores) of the Xeon E5-2603 with respect to one CPU core is only 3. 2×.
Price et al. (Tue,) studied this question.