Abstract
As the US Department of Energy (DOE) computing facilities began deploying petascale systems in 2008, DOE was already setting its sights on exascale. In that year, DARPA published a report on the feasibility of reaching exascale. The report authors identified several key challenges in the pursuit of exascale including power, memory, concurrency, and resiliency. That report informed the DOE's computing strategy for reaching exascale. With the deployment of Oak Ridge National Laboratory's Frontier supercomputer, we have officially entered the exascale era. In this paper, we discuss Frontier's architecture, how it addresses those challenges, and describe some early application results from Oak Ridge Leadership Computing Facility's Center of Excellence and the Exascale Computing Project.
Original language | English |
---|---|
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 |
---|
Conference
Conference | 2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 |
---|---|
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 joint project of the U.S. Department of Energy’s Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation’s exascale computing imperative. This material is based upon work supported by the CAMPA collaboration, a project of the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research and Office of High Energy Physics, Scientific Discovery through Advanced Computing (Sci-DAC) program. This work was supported by the Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory under U.S. Department of Energy Contract No. DE-AC02-05CH11231 and by LLNL under Contract DE-AC52-07NA27344. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101030214. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).