A dissection solver with kernel detection for symmetric finite element matrices on shared memory computers

SUMMARYA direct solver for symmetric sparse matrices from finite element problems is presented. The solver is supposed to work as a local solver of domain decomposition methods for hybrid parallelization on cluster systems of multi‐core CPUs, and then it is required to run on shared memory computers...

Full description

Saved in:
Bibliographic Details
Published inInternational journal for numerical methods in engineering Vol. 100; no. 2; pp. 136 - 164
Main Authors Suzuki, A., Roux, F.-X.
Format Journal Article
LanguageEnglish
Published Bognor Regis Blackwell Publishing Ltd 12.10.2014
Wiley Subscription Services, Inc
Wiley
Subjects
Online AccessGet full text
ISSN0029-5981
1097-0207
1097-0207
DOI10.1002/nme.4729

Cover

More Information
Summary:SUMMARYA direct solver for symmetric sparse matrices from finite element problems is presented. The solver is supposed to work as a local solver of domain decomposition methods for hybrid parallelization on cluster systems of multi‐core CPUs, and then it is required to run on shared memory computers and to have an ability of kernel detection. Symmetric pivoting with a given threshold factorizes a matrix with a decomposition introduced by a nested bisection and selects suspicious null pivots from the threshold. The Schur complement constructed from the suspicious null pivots is examined by a factorization with 1 × 1 and 2 × 2 pivoting and by a robust kernel detection algorithm based on measurement of residuals with orthogonal projections onto supposed image spaces. A static data structure from the nested bisection and a block sub‐structure for Schur complements at all bisection levels can use level 3 BLAS routines efficiently. Asynchronous task execution for each block can reduce idle time of processors drastically, and as a result, the solver has high parallel efficiency. Competitive performance of the developed solver to Intel Pardiso on shared memory computers is shown by numerical experiments. Copyright © 2014 John Wiley & Sons, Ltd.
Bibliography:ark:/67375/WNG-T54BTTV7-D
istex:E9A545A078E2F2469008FFCB357E8AD328213462
ArticleID:NME4729
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0029-5981
1097-0207
1097-0207
DOI:10.1002/nme.4729