An FMM Poisson solver for RAMSES is extended to adaptive mesh refinement and adaptive time stepping, matching multigrid accuracy while conserving momentum better across coarse-fine interfaces and scaling better in parallel.
Portability of Fortran's `do concurrent' on GPUs
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abstract
There is a continuing interest in using standard language constructs for accelerated computing in order to avoid (sometimes vendor-specific) external APIs. For Fortran codes, the {\tt do concurrent} (DC) loop has been successfully demonstrated on the NVIDIA platform. However, support for DC on other platforms has taken longer to implement. Recently, Intel has added DC GPU offload support to its compiler, as has HPE for AMD GPUs. In this paper, we explore the current portability of using DC across GPU vendors using the in-production solar surface flux evolution code, HipFT. We discuss implementation and compilation details, including when/where using directive APIs for data movement is needed/desired compared to using a unified memory system. The performance achieved on both data center and consumer platforms is shown.
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astro-ph.IM 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
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A Scalable Fast Multipole Method Poisson Solver for the RAMSES code: II. Adaptive Mesh Refinement and Adaptive Time Stepping
An FMM Poisson solver for RAMSES is extended to adaptive mesh refinement and adaptive time stepping, matching multigrid accuracy while conserving momentum better across coarse-fine interfaces and scaling better in parallel.