4.7 Article

EMMA: an adaptive mesh refinement cosmological simulation code with radiative transfer

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stv1896

关键词

methods: numerical; dark ages, reionization, first stars

资金

  1. Agence Nationale de la Recherche [ANR-12-JS05-0001, ANR-14-CE33-0016-03, ANR-09-BLAN-0030]
  2. Oak Ridge Leadership Computing Facility, Department of the Environment Office of Science [AST031, AST105, DE-AC05-00OR22725]
  3. Centre de Calcul Recherche et Technologie-CCRT, DARI Grant [2015047393]
  4. Agence Nationale de la Recherche (ANR) [ANR-12-JS05-0001, ANR-09-BLAN-0030] Funding Source: Agence Nationale de la Recherche (ANR)

向作者/读者索取更多资源

EMMA is a cosmological simulation code aimed at investigating the reionization epoch. It handles simultaneously collisionless and gas dynamics, as well as radiative transfer physics using a moment-based description with the M1 approximation. Field quantities are stored and computed on an adaptive three-dimensional mesh and the spatial resolution can be dynamically modified based on physically motivated criteria. Physical processes can be coupled at all spatial and temporal scales. We also introduce a new and optional approximation to handle radiation: the light is transported at the resolution of the non-refined grid and only once the dynamics has been fully updated, whereas thermo-chemical processes are still tracked on the refined elements. Such an approximation reduces the overheads induced by the treatment of radiation physics. A suite of standard tests are presented and passed by EMMA, providing a validation for its future use in studies of the reionization epoch. The code is parallel and is able to use graphics processing units (GPUs) to accelerate hydrodynamics and radiative transfer calculations. Depending on the optimizations and the compilers used to generate the CPU reference, global GPU acceleration factors between x3.9 and x16.9 can be obtained. Vectorization and transfer operations currently prevent better GPU performance and we expect that future optimizations and hardware evolution will lead to greater accelerations.

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