Abstract
The Simple Cloud-Resolving E3SM Atmosphere Model (Scream) won the inaugural ACM Gordon Bell Prize for Climate Modeling. While most of Scream is portable Kokkos code, the Gordon-Bell runs did include tuning specifically for Frontier, the exascale computer at Oak Ridge National Laboratory. Production science runs use the same high-level configuration of Scream, but the tuned kernels do not meet the software standards necessary to merge into the production code base. This work describes experiments to refactor these kernels to meet the maintainability requirements of the production Scream code base while preserving high performance.
| Original language | English |
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| Title of host publication | 2024 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 286-292 |
| Number of pages | 7 |
| ISBN (Electronic) | 9798350364606 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2024 - San Francisco, United States Duration: May 27 2024 → May 31 2024 |
Publication series
| Name | 2024 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2024 |
|---|
Conference
| Conference | 2024 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2024 |
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| Country/Territory | United States |
| City | San Francisco |
| Period | 05/27/24 → 05/31/24 |
Funding
The author performed most of this work while employed by Hewlett Packard Enterprise in the Frontier Center of Excellence. The author wishes to thank Scream developers Sarat Sreepathi, Mark Taylor, Peter Caldwell, Oksana Guba, Luca Bertagna, and Matt Norman. This research used resources of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
Keywords
- GPUs
- Kokkos
- performance;
- software maintainability