Assembly of FETI dual operator using CUDA

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10258738" target="_blank" >RIV/61989100:27740/25:10258738 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/11106042" target="_blank" >https://ieeexplore.ieee.org/document/11106042</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IPDPSW66978.2025.00062" target="_blank" >10.1109/IPDPSW66978.2025.00062</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Assembly of FETI dual operator using CUDA

Popis výsledku v původním jazyce

FETI is a numerical method used to solve engineering problems. It builds on the ideas of domain decomposition, which makes it highly scalable and capable of efficiently utilizing whole supercomputers. One of the most time-consuming parts of the FETI solver is the application of the dual operator F in every iteration of the solver.It is traditionally performed on the CPU using an implicit approach of applying the individual sparse matrices that form F right-to-left. Another approach is to apply the dual operator explicitly, which involves a simple dense matrix-vector multiplication and can be efficiently performed on the GPU. However, this requires additional preprocessing on the CPU where the dense matrix is assembled, which makes the explicit approach beneficial only after hundreds of iterations are performed.In this paper, we use the GPU to accelerate the assembly process as well. This significantly shortens the preprocessing time, thus decreasing the number of solver iterations needed to make the explicit approach beneficial.With a proper configuration, we only need a few tens of iterations to achieve speedup relative to the implicit CPU approach. Compared to the CPU-only explicit approach, we achieved up to 10× speedup for the preprocessing and 25× for the application.

Název v anglickém jazyce

Assembly of FETI dual operator using CUDA

Popis výsledku anglicky

FETI is a numerical method used to solve engineering problems. It builds on the ideas of domain decomposition, which makes it highly scalable and capable of efficiently utilizing whole supercomputers. One of the most time-consuming parts of the FETI solver is the application of the dual operator F in every iteration of the solver.It is traditionally performed on the CPU using an implicit approach of applying the individual sparse matrices that form F right-to-left. Another approach is to apply the dual operator explicitly, which involves a simple dense matrix-vector multiplication and can be efficiently performed on the GPU. However, this requires additional preprocessing on the CPU where the dense matrix is assembled, which makes the explicit approach beneficial only after hundreds of iterations are performed.In this paper, we use the GPU to accelerate the assembly process as well. This significantly shortens the preprocessing time, thus decreasing the number of solver iterations needed to make the explicit approach beneficial.With a proper configuration, we only need a few tens of iterations to achieve speedup relative to the implicit CPU approach. Compared to the CPU-only explicit approach, we achieved up to 10× speedup for the preprocessing and 25× for the application.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

—

Návaznosti

—

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název statě ve sborníku

2025 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2025 : proceedings : 3-7 June 2025 Milan, Italy

ISBN

979-8-3315-2644-3

ISSN

2639-3867

e-ISSN

2995-066X

Počet stran výsledku

10

Strana od-do

365-374

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Milán

Datum konání akce

3. 6. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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