Automated search of an optimal configuration of FETI-based algorithms with the swarm and evolutionary algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10256344" target="_blank" >RIV/61989100:27240/24:10256344 - isvavai.cz</a>
Alternative codes found
RIV/61989592:15410/24:73628329 RIV/61989100:27740/24:10256344
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1568494624012110?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1568494624012110?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.asoc.2024.112437" target="_blank" >10.1016/j.asoc.2024.112437</a>
Alternative languages
Result language
angličtina
Original language name
Automated search of an optimal configuration of FETI-based algorithms with the swarm and evolutionary algorithms
Original language description
Finite Element Tearing and Interconnecting (FETI) methods are used in the engineering community to solve extremely large engineering simulations on clusters and supercomputers with thousands of computational nodes. This paper focuses on minimizing the execution time of these methods by searching for an optimal configuration with swarm and evolutionary algorithms (SEAs). It incorporates optimization of an expensive cost function (taking tens to hundreds of seconds) of discrete search space with up to hundreds of thousands of combinations constrained by its boundaries and incompatible individuals (invalid combination of FETI solver parameters). In addition, the optimization occurs in real time, i.e., during a simulation. Hence, the number of objective function evaluations must remain low (tens to lower hundreds). The paper compares the performance of 3 basic SEAs with a reduced population size (Differential Evolution, Particle Swarm Optimization, and Self-Organizing Migrating Algorithm), 4 micro SEAs (Micro Differential Evolution Ray, Improved Micro-Particle Swarm Optimization, Micro-Particle Swarm Optimization, and Micro-Genetic Algorithm), and a random search on 4 distinct time-dependent simulations of a heat transfer. The experiments show that basic SEAs with a small population (about 5 individuals) and a penalty system as protection against incompatible configurations represent the most effective solution. One can use them to find the optimal configuration of FETI-based methods in approximately 130 evaluations. It can improve the utilization of expensive hardware resources of modern computational clusters.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Soft Computing
ISSN
1568-4946
e-ISSN
1872-9681
Volume of the periodical
167
Issue of the periodical within the volume
December
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
16
Pages from-to
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UT code for WoS article
001361443400001
EID of the result in the Scopus database
2-s2.0-85209370135