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Phoebus: Performance Portable GRRMHD for Relativistic Astrophysics

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arxiv 2410.09146 v2 pith:ULXTX6LH submitted 2024-10-11 astro-ph.HE astro-ph.IMastro-ph.SRphysics.comp-ph

classification astro-ph.HEastro-ph.IMastro-ph.SRphysics.comp-ph
keywords phoebusmethodsrelativisticastrophysicaldemonstrategeneralperformanceportable
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We introduce the open source code PHOEBUS (phifty one ergs blows up a star) for astrophysical general relativistic radiation magnetohydrodynamic simulations. PHOEBUS is designed for, but not limited to, high energy astrophysical environments such as core-collapse supernovae, neutron star mergers, black-hole accretion disks, and similar phenomena. General relativistic magnetohydrodynamics are modeled in the Valencia formulation with conservative finite volume methods. Neutrino radiation transport is included with Monte Carlo and moment methods. PHOEBUS is built on the PARTHENON (Grete et al. 2022) performance portable adaptive mesh refinement framework, uses a GPU first development strategy, and is capable of modeling a large dynamic range in space and time. PHOEBUS utilizes KOKKOS for on-node parallelism and supports both CPU and GPU architectures. We describe the physical model employed in PHOEBUS, the numerical methods used, and demonstrate a suite of test problems to showcase its abilities. We demonstrate weak scaling to over 500 H100 GPUs.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Not-Quite-Transcendental Functions For Logarithmic Interpolation of Tabulated Data

    physics.comp-ph 2025-01 conditional novelty 5.0 of 10

    Second-order NQT functions, a C^1 piecewise quadratic approximation to log2, preserve second-order convergence of linear interpolation on logarithmic grids while running faster than true logarithms.

  2. SACRA-K: A Performance-Portable Numerical Relativity Code with Kokkos

    astro-ph.HE 2026-07 accept novelty 4.0 of 10

    A Kokkos-based C++ port of the SACRA numerical relativity code achieves ~10x speedup on GPU/APU over the Fortran CPU version while preserving waveform accuracy, pi-symmetry, and second-order convergence.

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