Abstract
The advent of Exascale computing invites an assessment of existing best practices for developing application readiness on the world's largest supercomputers. This work details observations from the last four years in preparing scientific applications to run on the Oak Ridge Leadership Computing Facility's (OLCF) Frontier system. This paper addresses a range of topics in software including programmability, tuning, and portability considerations that are key to moving applications from existing systems to future installations. A set of representative workloads provides case studies for general system and software testing. We evaluate the use of early access systems for development across several generations of hardware. Finally, we discuss how best practices were identified and disseminated to the community through a wide range of activities including user-guides and trainings. We conclude with recommendations for ensuring application readiness on future leadership computing systems.
Original language | English |
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Title of host publication | Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 |
Publisher | Association for Computing Machinery, Inc |
ISBN (Electronic) | 9798400701092 |
DOIs | |
State | Published - Nov 12 2023 |
Event | 2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 - Denver, United States Duration: Nov 12 2023 → Nov 17 2023 |
Publication series
Name | Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 |
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Conference
Conference | 2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 |
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Country/Territory | United States |
City | Denver |
Period | 11/12/23 → 11/17/23 |
Funding
This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the DOE Office of Science (SC) and the NNSA, and was performed using computational resources of the Oak Ridge Leadership Computing Facility, which is a DOE SC User Facility supported under Contract DE-AC05-00OR22725 This manuscript has been co-authored by Oak Ridge National Laboratory, operated by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S.Department of Energy. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan.