Utilizing Sparsity in the GPU-accelerated Assembly of Schur Complement Matrices in Domain Decomposition Methods

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10259205" target="_blank" >RIV/61989100:27740/25:10259205 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1145/3712285.3759904" target="_blank" >https://doi.org/10.1145/3712285.3759904</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3712285.3759904" target="_blank" >10.1145/3712285.3759904</a>

Result language

angličtina

Original language name

Utilizing Sparsity in the GPU-accelerated Assembly of Schur Complement Matrices in Domain Decomposition Methods

Original language description

Schur complement matrices emerge in many domain decomposition methods that can utilize supercomputers to solve complex engineering problems. As most of today&apos;s high-performance clusters&apos; performance lies in GPUs, these methods should also be accelerated. Typically, the offloaded components are the explicitly assembled dense Schur complement matrices used later in the iterative solver for multiplication with a vector. As the explicit assembly is expensive, it adds a significant overhead to this approach of acceleration. It has already been shown that the overhead can be minimized by assembling the Schur complements directly on the GPU. This paper shows that the GPU assembly can be further improved by wisely utilizing the matrix sparsity. In the context of FETI, we achieved a speedup of 5.1 in the GPU section of the code and 3.3 for the whole assembly, making the acceleration beneficial from as few as 10 iterations for subdomains with 1,000-70,000 unknowns.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

—

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025 :16-21 Nov 2025 : St. Louis, MO, USA

ISBN

979-8-4007-1466-5

ISSN

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e-ISSN

—

Number of pages

13

Pages from-to

1464-1476

Publisher name

Association for Computing Machinery

Place of publication

New York

Event location

St. Louis

Event date

Nov 16, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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