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The MURaM (Max Planck University of Chicago Radiative MHD) code is a solaratmosphere radiative MHD model that has been broadly applied to solar phenomenaranging from quiet to active sun, including eruptive events such as flares andcoronal mass ejections. The treatment of physics is sufficiently realistic toallow for the synthesis of emission from visible light to extreme UV andX-rays, which is critical for a detailed comparison with available and futuremulti-wavelength observations. This component relies critically on theradiation transport solver (RTS) of MURaM; the most computationally intensivecomponent of the code. The benefits of accelerating RTS are multiple fold: Afaster RTS allows for the regular use of the more expensive multi-bandradiation transport needed for comparison with observations, and this will pavethe way for the acceleration of ongoing improvements in RTS that are criticalfor simulations of the solar chromosphere. We present challenges and strategiesto accelerate a multi-physics, multi-band MURaM using a directive-basedprogramming model, OpenACC in order to maintain a single source code acrossCPUs and GPUs. Results for a $288^3$ test problem show that MURaM with theoptimized RTS routine achieves 1.73x speedup using a single NVIDIA V100 GPUover a fully subscribed 40-core Intel Skylake CPU node and with respect to thenumber of simulation points (in millions) per second, a single NVIDIA V100 GPUis equivalent to 69 Skylake cores. We also measure parallel performance on upto 96 GPUs and present weak and strong scaling results.

Refactoring the MPS/University of Chicago Radiative MHD(MURaM) Model for GPU/CPU Performance Portability Using OpenACC Directives