AsterX: a new open-source GPU-accelerated GRMHD code for dynamical spacetimes
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arXiv
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866929708430524416 |
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| author | Kalinani, Jay V. Ji, Liwei Ennoggi, Lorenzo Armengol, Federico G. Lopez Sanches, Lucas Timotheo Tsao, Bing-Jyun Brandt, Steven R Campanelli, Manuela Ciolfi, Riccardo Giacomazzo, Bruno Haas, Roland Schnetter, Erik Zlochower, Yosef |
| author_facet | Kalinani, Jay V. Ji, Liwei Ennoggi, Lorenzo Armengol, Federico G. Lopez Sanches, Lucas Timotheo Tsao, Bing-Jyun Brandt, Steven R Campanelli, Manuela Ciolfi, Riccardo Giacomazzo, Bruno Haas, Roland Schnetter, Erik Zlochower, Yosef |
| contents | We present AsterX, a novel open-source, modular, GPU-accelerated, fully general relativistic magnetohydrodynamic (GRMHD) code designed for dynamic spacetimes in 3D Cartesian coordinates, and tailored for exascale computing. We utilize block-structured adaptive mesh refinement (AMR) through CarpetX, the new driver for the Einstein Toolkit, which is built on AMReX, a software framework for massively parallel applications. AsterX employs the Valencia formulation for GRMHD, coupled with the Z4c formalism for spacetime evolution, while incorporating high resolution shock capturing schemes to accurately handle the hydrodynamics. AsterX has undergone rigorous testing in both static and dynamic spacetime, demonstrating remarkable accuracy and agreement with other codes in literature. Using subcycling in time, we find an overall performance gain of factor 2.5 to 4.5. Benchmarking the code through scaling tests on OLCF's Frontier supercomputer, we demonstrate a weak scaling efficiency of about 67%-77% on 4096 nodes compared to an 8-node performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_11669 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AsterX: a new open-source GPU-accelerated GRMHD code for dynamical spacetimes Kalinani, Jay V. Ji, Liwei Ennoggi, Lorenzo Armengol, Federico G. Lopez Sanches, Lucas Timotheo Tsao, Bing-Jyun Brandt, Steven R Campanelli, Manuela Ciolfi, Riccardo Giacomazzo, Bruno Haas, Roland Schnetter, Erik Zlochower, Yosef High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology We present AsterX, a novel open-source, modular, GPU-accelerated, fully general relativistic magnetohydrodynamic (GRMHD) code designed for dynamic spacetimes in 3D Cartesian coordinates, and tailored for exascale computing. We utilize block-structured adaptive mesh refinement (AMR) through CarpetX, the new driver for the Einstein Toolkit, which is built on AMReX, a software framework for massively parallel applications. AsterX employs the Valencia formulation for GRMHD, coupled with the Z4c formalism for spacetime evolution, while incorporating high resolution shock capturing schemes to accurately handle the hydrodynamics. AsterX has undergone rigorous testing in both static and dynamic spacetime, demonstrating remarkable accuracy and agreement with other codes in literature. Using subcycling in time, we find an overall performance gain of factor 2.5 to 4.5. Benchmarking the code through scaling tests on OLCF's Frontier supercomputer, we demonstrate a weak scaling efficiency of about 67%-77% on 4096 nodes compared to an 8-node performance. |
| title | AsterX: a new open-source GPU-accelerated GRMHD code for dynamical spacetimes |
| topic | High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2406.11669 |