Enabling GPU Accelerated Computing in the SUNDIALS Time Integration Library

As part of the Exascale Computing Project (ECP), a recent focus of development efforts for the SUite of Nonlinear and DIfferential/ALgebraic equation Solvers (SUNDIALS) has been to enable GPU-accelerated time integration in scientific applications at extreme scales. This effort has resulted in sever...

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Bibliographic Details
Published inarXiv.org
Main Authors Balos, Cody J, Gardner, David J, Woodward, Carol S, Reynolds, Daniel R
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 08.12.2021
Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Computer Science - Mathematical Software
Data structures
Differential equations
Supercomputers
Time integration
Utilities
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Summary:As part of the Exascale Computing Project (ECP), a recent focus of development efforts for the SUite of Nonlinear and DIfferential/ALgebraic equation Solvers (SUNDIALS) has been to enable GPU-accelerated time integration in scientific applications at extreme scales. This effort has resulted in several new GPU-enabled implementations of core SUNDIALS data structures, support for programming paradigms which are aware of the heterogeneous architectures, and the introduction of utilities to provide new points of flexibility. In this paper, we discuss our considerations, both internal and external, when designing these new features and present the features themselves. We also present performance results for several of the features on the Summit supercomputer and early access hardware for the Frontier supercomputer, which demonstrate negligible performance overhead resulting from the additional infrastructure and significant speedups when using both NVIDIA and AMD GPUs.
ISSN:2331-8422
DOI:10.48550/arxiv.2011.12984