Quokka: A code for two-moment AMR radiation hydrodynamics on GPUs. (arXiv:2110.01792v2 [astro-ph.IM] UPDATED)
<a href="http://arxiv.org/find/astro-ph/1/au:+Wibking_B/0/1/0/all/0/1">Benjamin D. Wibking</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Krumholz_M/0/1/0/all/0/1">Mark R. Krumholz</a>
We present Quokka, a new subcycling-in-time, block-structured adaptive mesh
refinement (AMR) radiation hydrodynamics code optimised for graphics processing
units (GPUs). Quokka solves the equations of hydrodynamics with the piecewise
parabolic method (PPM) in a method-of-lines formulation, and handles radiative
transfer via the variable Eddington tensor (VET) radiation moment equations
with a local closure. We use the AMReX library to handle the adaptive mesh
management. In order to maximise GPU performance, we combine explicit-in-time
evolution of the radiation moment equations with the reduced speed-of-light
approximation. We show results for a wide range of test problems for
hydrodynamics, radiation, and coupled radiation hydrodynamics. On uniform grids
in 3D on a single GPU, our code achieves > 250 million hydrodynamic updates per
second and almost 40 million radiation hydrodynamic updates per second. For
radiation hydrodynamics problems on uniform grids in 3D, our code scales from 4
GPUs to 256 GPUs with an efficiency of 76 per cent. The code is publicly
released under an open-source license on GitHub.
We present Quokka, a new subcycling-in-time, block-structured adaptive mesh
refinement (AMR) radiation hydrodynamics code optimised for graphics processing
units (GPUs). Quokka solves the equations of hydrodynamics with the piecewise
parabolic method (PPM) in a method-of-lines formulation, and handles radiative
transfer via the variable Eddington tensor (VET) radiation moment equations
with a local closure. We use the AMReX library to handle the adaptive mesh
management. In order to maximise GPU performance, we combine explicit-in-time
evolution of the radiation moment equations with the reduced speed-of-light
approximation. We show results for a wide range of test problems for
hydrodynamics, radiation, and coupled radiation hydrodynamics. On uniform grids
in 3D on a single GPU, our code achieves > 250 million hydrodynamic updates per
second and almost 40 million radiation hydrodynamic updates per second. For
radiation hydrodynamics problems on uniform grids in 3D, our code scales from 4
GPUs to 256 GPUs with an efficiency of 76 per cent. The code is publicly
released under an open-source license on GitHub.
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