Technical note: A successive over-relaxation preconditioner to solve mixed model equations for genetic evaluation

A computationally efficient preconditioned conjugate gradient algorithm with a symmetric successive over-relaxation (SSOR) preconditioner for the iterative solution of set mixed model equations is described. The potential computational savings of this approach are examined for an example of single-s...

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Bibliographic Details
Published inJournal of animal science Vol. 94; no. 11; pp. 4530 - 4535
Main Author Meyer, K
Format Journal Article
LanguageEnglish
Published United States 01.11.2016
Subjects
Algorithms
Animals
Australia
Genome
Genomics
Models, Genetic
Sheep - genetics
Software
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Summary:A computationally efficient preconditioned conjugate gradient algorithm with a symmetric successive over-relaxation (SSOR) preconditioner for the iterative solution of set mixed model equations is described. The potential computational savings of this approach are examined for an example of single-step genomic evaluation of Australian sheep. Results show that the SSOR preconditioner can substantially reduce the number of iterates required for solutions to converge compared with simpler preconditioners with marked reductions in overall computing time.
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ISSN:1525-3163
DOI:10.2527/jas.2016-0665