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Exascale Computing in the United States

Published: 01 January 2019 Publication History

Abstract

The U.S. is a long-time international leader in HPC, rooted in a strong and innovative computing industry that is complemented by partnerships with and among federal agencies, academia, and industries whose success relies on HPC. The advent of exascale computing brings challenges in traditional simulation as well as in areas colloquially referred to as “Big Data.” Within this context, we describe the U.S. exascale computing strategy: 1) the National Strategic Computing Initiative, a multiple U.S. federal agency effort comprehensively addressing computing and computational science requirements in the U.S.; 2) the Exascale Computing Initiative, a DOE effort to acquire, develop, and deploy exascale computing platforms within DOE laboratories on a given timeline; and, 3) the Exascale Computing Project (a component of the Exascale Computing Initiative), dedicated to the creation and enhancement of applications, software, and hardware technologies for exascale computers, focused on vital U.S. national security and science needs.

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  • (2024)Deploying Optimized Scientific and Engineering Applications on Exascale SystemsComputing in Science and Engineering10.1109/MCSE.2024.339720926:1(41-47)Online publication date: 1-Jan-2024
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Information & Contributors

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Published In

cover image Computing in Science and Engineering
Computing in Science and Engineering  Volume 21, Issue 1
January 2019
104 pages

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IEEE Educational Activities Department

United States

Publication History

Published: 01 January 2019

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Cited By

View all
  • (2024)ECP libraries and toolsInternational Journal of High Performance Computing Applications10.1177/1094342024127100538:5(381-408)Online publication date: 1-Sep-2024
  • (2024)Transforming Science Through Software: Improving While Delivering 100×Computing in Science and Engineering10.1109/MCSE.2024.340046226:1(4-7)Online publication date: 1-Jan-2024
  • (2024)Deploying Optimized Scientific and Engineering Applications on Exascale SystemsComputing in Science and Engineering10.1109/MCSE.2024.339720926:1(41-47)Online publication date: 1-Jan-2024
  • (2024)Scalable Delivery of Scalable Libraries and Tools: How ECP Delivered a Software Ecosystem for Exascale and BeyondComputing in Science and Engineering10.1109/MCSE.2024.338493726:1(9-18)Online publication date: 1-Jan-2024
  • (2024)DAG-based workflows scheduling using Actor–Critic Deep Reinforcement LearningFuture Generation Computer Systems10.1016/j.future.2023.09.018150:C(354-363)Online publication date: 1-Jan-2024
  • (2023)Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel GenerationProceedings of the 52nd International Conference on Parallel Processing Workshops10.1145/3605731.3605886(136-144)Online publication date: 7-Aug-2023
  • (2023)Sparbit: Towards to a Logarithmic-Cost and Data Locality-Aware MPI Allgather AlgorithmJournal of Grid Computing10.1007/s10723-023-09650-521:2Online publication date: 16-Mar-2023
  • (2022)DayDreamProceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis10.5555/3571885.3571914(1-18)Online publication date: 13-Nov-2022
  • (2022)Batched Graph Community Detection on GPUsProceedings of the International Conference on Parallel Architectures and Compilation Techniques10.1145/3559009.3569655(172-184)Online publication date: 8-Oct-2022
  • (2022)Online Application Guidance for Heterogeneous Memory SystemsACM Transactions on Architecture and Code Optimization10.1145/353385519:3(1-27)Online publication date: 6-Jul-2022
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