Benchmarking with Supernovae: A Performance Study of the FLASH Code
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arXiv
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| Autores principales: | , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
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| _version_ | 1866929478219857920 |
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| author | Martin, Joshua Feldman, Catherine Siegmann, Eva Curtis, Tony Carlson, David Coskun, Firat Wood, Daniel Gonzalez, Raul Harrison, Robert J. Calder, Alan C. |
| author_facet | Martin, Joshua Feldman, Catherine Siegmann, Eva Curtis, Tony Carlson, David Coskun, Firat Wood, Daniel Gonzalez, Raul Harrison, Robert J. Calder, Alan C. |
| contents | Astrophysical simulations are computation, memory, and thus energy intensive, thereby requiring new hardware advances for progress. Stony Brook University recently expanded its computing cluster "SeaWulf" with an addition of 94 new nodes featuring Intel Sapphire Rapids Xeon Max series CPUs. We present a performance and power efficiency study of this hardware performed with FLASH: a multi-scale, multi-physics, adaptive mesh-based software instrument. We extend this study to compare performance to that of Stony Brook's Ookami testbed which features ARM-based A64FX-700 processors, and SeaWulf's AMD EPYC Milan and Intel Skylake nodes. Our application is a stellar explosion known as a thermonuclear (Type Ia) supernova and for this 3D problem, FLASH includes operators for hydrodynamics, gravity, and nuclear burning, in addition to routines for the material equation of state. We perform a strong-scaling study with a 220 GB problem size to explore both single- and multi-node performance. Our study explores the performance of different MPI mappings and the distribution of processors across nodes. From these tests, we determined the optimal configuration to balance runtime and energy consumption for our application. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_16084 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Benchmarking with Supernovae: A Performance Study of the FLASH Code Martin, Joshua Feldman, Catherine Siegmann, Eva Curtis, Tony Carlson, David Coskun, Firat Wood, Daniel Gonzalez, Raul Harrison, Robert J. Calder, Alan C. Distributed, Parallel, and Cluster Computing Instrumentation and Methods for Astrophysics Astrophysical simulations are computation, memory, and thus energy intensive, thereby requiring new hardware advances for progress. Stony Brook University recently expanded its computing cluster "SeaWulf" with an addition of 94 new nodes featuring Intel Sapphire Rapids Xeon Max series CPUs. We present a performance and power efficiency study of this hardware performed with FLASH: a multi-scale, multi-physics, adaptive mesh-based software instrument. We extend this study to compare performance to that of Stony Brook's Ookami testbed which features ARM-based A64FX-700 processors, and SeaWulf's AMD EPYC Milan and Intel Skylake nodes. Our application is a stellar explosion known as a thermonuclear (Type Ia) supernova and for this 3D problem, FLASH includes operators for hydrodynamics, gravity, and nuclear burning, in addition to routines for the material equation of state. We perform a strong-scaling study with a 220 GB problem size to explore both single- and multi-node performance. Our study explores the performance of different MPI mappings and the distribution of processors across nodes. From these tests, we determined the optimal configuration to balance runtime and energy consumption for our application. |
| title | Benchmarking with Supernovae: A Performance Study of the FLASH Code |
| topic | Distributed, Parallel, and Cluster Computing Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2408.16084 |