TY - GEN
T1 - Benchmarking with Supernovae
T2 - 2024 Practice and Experience in Advanced Research Computing, PEARC 2024
AU - Martin, Joshua Ezekiel
AU - Feldman, Catherine
AU - Calder, Alan
AU - Curtis, Tony
AU - Siegmann, Eva
AU - Carlson, David
AU - Gonzalez, Raul
AU - Wood, Daniel
AU - Harrison, Robert
AU - Coskun, Firat
N1 - Publisher Copyright:
© 2024 Owner/Author.
PY - 2024/7/17
Y1 - 2024/7/17
N2 - 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.
AB - 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.
KW - A64FX
KW - Multi-scale
KW - Performance analysis
KW - Sapphire Rapids
KW - multi-physics simulation
UR - https://www.scopus.com/pages/publications/85200404236
U2 - 10.1145/3626203.3670536
DO - 10.1145/3626203.3670536
M3 - Conference contribution
AN - SCOPUS:85200404236
T3 - PEARC 2024 - Practice and Experience in Advanced Research Computing 2024: Human Powered Computing
BT - PEARC 2024 - Practice and Experience in Advanced Research Computing 2024
PB - Association for Computing Machinery, Inc
Y2 - 21 July 2024 through 25 July 2024
ER -