TY - GEN
T1 - Performance of an Astrophysical Radiation Hydrodynamics Code under Scalable Vector Extension Optimization
AU - Smolarski, Dennis C.
AU - Swesty, F. Douglas
AU - Calder, Alan C.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - We present results of a performance study of an astrophysical radiation hydrodynamics code, V2D, on the Arm-based A64FX processor developed by Fujitsu. The code solves sparse linear systems, a task for which the A64FX architecture should be well suited. We performed the performance analysis study on Ookami, an Apollo 80 platform utilizing the A64FX processor. We explored several compilers and performance anal-ysis packages and found the code did not perform as expected under scalable vector extension optimization, suggesting that a 'deeper dive' into analyzing the code is worthwhile. However, a simple driver program that exercised basic sparse linear algebra routines used by V2D did show significant speedup with the use of the scalable vector extension optimization. We present the initial results from the study which used V2D on a relatively simple test problem that emphasized the repeated solution of sparse linear systems.
AB - We present results of a performance study of an astrophysical radiation hydrodynamics code, V2D, on the Arm-based A64FX processor developed by Fujitsu. The code solves sparse linear systems, a task for which the A64FX architecture should be well suited. We performed the performance analysis study on Ookami, an Apollo 80 platform utilizing the A64FX processor. We explored several compilers and performance anal-ysis packages and found the code did not perform as expected under scalable vector extension optimization, suggesting that a 'deeper dive' into analyzing the code is worthwhile. However, a simple driver program that exercised basic sparse linear algebra routines used by V2D did show significant speedup with the use of the scalable vector extension optimization. We present the initial results from the study which used V2D on a relatively simple test problem that emphasized the repeated solution of sparse linear systems.
KW - astrophysics
KW - computer architecture
KW - exascale
KW - high-performance computing
KW - linear algebra
UR - https://www.scopus.com/pages/publications/85140873727
U2 - 10.1109/CLUSTER51413.2022.00071
DO - 10.1109/CLUSTER51413.2022.00071
M3 - Conference contribution
AN - SCOPUS:85140873727
T3 - Proceedings - IEEE International Conference on Cluster Computing, ICCC
SP - 545
EP - 548
BT - Proceedings - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022
Y2 - 6 September 2022 through 9 September 2022
ER -