Improved and vectorised matlab-based algorithms for serial and parallel implementation of finite element method in linear elasticity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F24%3A39921520" target="_blank" >RIV/00216275:25510/24:39921520 - isvavai.cz</a>
Result on the web
<a href="https://www.iitf.lbtu.lv/conference/proceedings2024/Papers/TF212.pdf" target="_blank" >https://www.iitf.lbtu.lv/conference/proceedings2024/Papers/TF212.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.22616/ERDev.2024.23.TF212" target="_blank" >10.22616/ERDev.2024.23.TF212</a>
Alternative languages
Result language
angličtina
Original language name
Improved and vectorised matlab-based algorithms for serial and parallel implementation of finite element method in linear elasticity
Original language description
This paper presents two improved algorithms for efficient sequential and parallel implementation of the Finite element method (FEM) for both linear and nonlinear boundary value problems. The proposed algorithms address some weak points, such as the overuse of for-loops and serial computing caused by dependencies in constructing fundamental expressions (global stiffness matrix, mass matrix, global force vector, etc.) resulting from the finite element method. By taking advantage of the concepts of sparse matrix representation, vectorization, and the physical architecture of modern computing resources, the proposed methods are free from mesh partitioning techniques or similar approaches and enable the use of all available CPU cores/threads without synchronization. Moreover, these algorithms are also adapted to deal with meshes involving elements of any order in both 2D and 3D. Two tests from NAFEMS benchmarks are implemented in MATLAB to verify the accuracy and stability of the proposed algorithms in both serial and parallel processing. According to serial and parallel computing results, the proposed algorithms perform better than the standard sparse assembly strategy and behave linearly with the mesh size but at a smaller rate than the latter. In parallel processing, the algorithms are also demonstrated to be accurate and achieve an efficiency of at least 60% in 2D and 70% with two cores/threads when the mesh size is greater than 10,000. Moreover, the simulations revealed that the performance gap between the proposed algorithm and the classical sparse algorithm is more pronounced in 2D than in 3D due to the increase in degrees of freedom.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20104 - Transport engineering
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
Article name in the collection
Engineering for Rural Development
ISBN
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ISSN
1691-3043
e-ISSN
1691-5976
Number of pages
10
Pages from-to
1032-1041
Publisher name
Latvia University of Afgriculture
Place of publication
Jelgava
Event location
Jelgava
Event date
May 22, 2024
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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