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Performance comparison of data‐reordering algorithms for sparse matrix–vector multiplication in edge‐based unstructured grid computations
Author(s) -
Coutinho Alvaro L. G. A.,
Martins Marcos A. D.,
Sydenstricker Rubens M.,
Elias Renato N.
Publication year - 2006
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.1557
Subject(s) - pentium , computer science , parallel computing , benchmark (surveying) , computation , algorithm , sparse matrix , multiplication (music) , polygon mesh , matrix multiplication , computational science , enhanced data rates for gsm evolution , grid , mathematics , computer graphics (images) , geometry , physics , quantum mechanics , combinatorics , gaussian , telecommunications , geodesy , quantum , geography
Several performance improvements for finite‐element edge‐based sparse matrix–vector multiplication algorithms on unstructured grids are presented and tested. Edge data structures for tetrahedral meshes and triangular interface elements are treated, focusing on nodal and edges renumbering strategies for improving processor and memory hierarchy use. Benchmark computations on Intel Itanium 2 and Pentium IV processors are performed. The results show performance improvements in CPU time ranging from 2 to 3. Copyright © 2005 John Wiley & Sons, Ltd.