Ginkgo - A math library designed to accelerate Exascale Computing Project science applications

Large-scale simulations require efficient computation across the entire computing hierarchy. A challenge of the Exascale Computing Project (ECP) was to reconcile highly heterogeneous hardware with the myriad of applications that were required to run on these supercomputers. Mathematical software forms the backbone of almost all scientific applications, providing efficient abstractions and operations that are crucial to harness the performance of computing systems. Ginkgo is one such mathematical software library, nurtured by ECP, providing high-performance, user-friendly, and performance portable interfaces for applications in ECP and beyond. In this paper, we elaborate on Ginkgo’s philosophy of high-performance software that is sustainable, reproducible, and easy to use. We showcase the wide feature set of solvers and preconditioners available in Ginkgo and the central concepts involved in their design. We elaborate on four different ECP software integrations: MFEM, PeleLM + SUNDIALS, XGC, and ExaSGD that use Ginkgo to accelerate their science runs. Performance studies of different problems from these applications highlight the effectiveness of Ginkgo and the benefits incurred by these ECP applications.

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Publication Details

Journal
The International Journal of High Performance Computing Applications
Published
2024-08-20
DOI
https://doi.org/10.1177/10943420241268323
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Ginkgo - A math library designed to accelerate Exascale Computing Project science applications

Hartwig Anzt, Yu‐Hsiang Tsai, Terry Cojean, Natalie Beams et al.
The International Journal of High Performance Computing Applications
Distributed and Parallel Computing Systems
article

Ginkgo - A math library designed to accelerate Exascale Computing Project science applications

Hartwig Anzt, Yu‐Hsiang Tsai, Terry Cojean, Natalie Beams, Tobias Ribizel, Pratik Nayak, Marcel Koch, Fritz Göbel, Thomas Grützmacher
article en

Abstract

Large-scale simulations require efficient computation across the entire computing hierarchy. A challenge of the Exascale Computing Project (ECP) was to reconcile highly heterogeneous hardware with the myriad of applications that were required to run on these supercomputers. Mathematical software forms the backbone of almost all scientific applications, providing efficient abstractions and operations that are crucial to harness the performance of computing systems. Ginkgo is one such mathematical software library, nurtured by ECP, providing high-performance, user-friendly, and performance portable interfaces for applications in ECP and beyond. In this paper, we elaborate on Ginkgo’s philosophy of high-performance software that is sustainable, reproducible, and easy to use. We showcase the wide feature set of solvers and preconditioners available in Ginkgo and the central concepts involved in their design. We elaborate on four different ECP software integrations: MFEM, PeleLM + SUNDIALS, XGC, and ExaSGD that use Ginkgo to accelerate their science runs. Performance studies of different problems from these applications highlight the effectiveness of Ginkgo and the benefits incurred by these ECP applications.

The International Journal of High Performance Computing ApplicationsVol. 38(6)
Karlsruhe Institute of Technology (DE), Heilbronn University (DE), University of Tennessee at Knoxville (US)
Office of Science
Openalex Percentile: Top 86%
Distributed and Parallel Computing Systems
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