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Revision as of 17:32, 11 March 2021
Abstract
Software development for high-performance scientific computing continues to evolve in response to increased parallelism and the advent of on-node accelerators, in particular GPUs. While these hardware advancements have the potential to significantly reduce turnaround times, they also present implementation and design challenges for engineering codes. We investigate the use of two strategies to mitigate these challenges: the Kokkos library for performance portability across disparate architectures, and the
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Published on 10/03/21
Submitted on 10/03/21
Volume 1400 - Software, High Performance Computing, 2021
DOI: 10.23967/wccm-eccomas.2020.164
Licence: CC BY-NC-SA license
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