Efficient in-score sparse direct solution of large finite element problems
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388998%3A_____%2F14%3A00430422" target="_blank" >RIV/61388998:_____/14:00430422 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Efficient in-score sparse direct solution of large finite element problems
Popis výsledku v původním jazyce
Sparse direct solvers represent one of the possible approaches to the solution of large problems in FEM. Our approach focuses on minimizing the amount of storage space and computational time required for the solution of a large problem. This is achievedparticularly by using a modified minimum ordering algorithm to reduce the fill-in, therefore, reducing the number of numerical operations needed to compute the solution. Both the factorization and the backsubstitution algorithms are parallelized using the OpenMP library to fully exploit today's multi-core and multi-processor computers. The global stiffness matrix is assembled and stored in-core throughout the computation, using an efficient sparse matrix storage format. We present some details of our sparse direct solver implementation, realized within the framework of our in-house finite element code PMD. We also show the performance results for several large real-world problems taken from the engineering practice and assess the scalab
Název v anglickém jazyce
Efficient in-score sparse direct solution of large finite element problems
Popis výsledku anglicky
Sparse direct solvers represent one of the possible approaches to the solution of large problems in FEM. Our approach focuses on minimizing the amount of storage space and computational time required for the solution of a large problem. This is achievedparticularly by using a modified minimum ordering algorithm to reduce the fill-in, therefore, reducing the number of numerical operations needed to compute the solution. Both the factorization and the backsubstitution algorithms are parallelized using the OpenMP library to fully exploit today's multi-core and multi-processor computers. The global stiffness matrix is assembled and stored in-core throughout the computation, using an efficient sparse matrix storage format. We present some details of our sparse direct solver implementation, realized within the framework of our in-house finite element code PMD. We also show the performance results for several large real-world problems taken from the engineering practice and assess the scalab
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
JC - Počítačový hardware a software
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2014
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů