  The MURaM (Max Planck University of Chicago Radiative MHD) code is a solar
atmosphere radiative MHD model that has been broadly applied to solar phenomena
ranging from quiet to active sun, including eruptive events such as flares and
coronal mass ejections. The treatment of physics is sufficiently realistic to
allow for the synthesis of emission from visible light to extreme UV and
X-rays, which is critical for a detailed comparison with available and future
multi-wavelength observations. This component relies critically on the
radiation transport solver (RTS) of MURaM; the most computationally intensive
component of the code. The benefits of accelerating RTS are multiple fold: A
faster RTS allows for the regular use of the more expensive multi-band
radiation transport needed for comparison with observations, and this will pave
the way for the acceleration of ongoing improvements in RTS that are critical
for simulations of the solar chromosphere. We present challenges and strategies
to accelerate a multi-physics, multi-band MURaM using a directive-based
programming model, OpenACC in order to maintain a single source code across
CPUs and GPUs. Results for a $288^3$ test problem show that MURaM with the
optimized RTS routine achieves 1.73x speedup using a single NVIDIA V100 GPU
over a fully subscribed 40-core Intel Skylake CPU node and with respect to the
number of simulation points (in millions) per second, a single NVIDIA V100 GPU
is equivalent to 69 Skylake cores. We also measure parallel performance on up
to 96 GPUs and present weak and strong scaling results.
