Technical note: A successive over-relaxation preconditioner to solve mixed model equations for genetic evaluation.
Saved in:
| Title: | Technical note: A successive over-relaxation preconditioner to solve mixed model equations for genetic evaluation. |
|---|---|
| Authors: | Meyer, K.1 |
| Source: | Journal of Animal Science. Nov2016, Vol. 94 Issue 11, p4530-4535. 6p. 1 Chart. |
| Document Type: | Article |
| Subjects: | Sheep genetics, Genomics, Computing platforms, Animal breeding, Algorithms |
| Author-Supplied Keywords: | computational requirements genetic evaluation preconditioned conjugate gradient algorithm symmetric successive over-relaxation preconditioner |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Animal Science is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Author Affiliations: | 1Animal Genetics and Breeding Unit, University of New England, Armidale NSW 2351, Australia. |
| ISSN: | 0021-8812 |
| DOI: | 10.2527/jas.2016-0665 |
| Accession Number: | 119438348 |
| Database: | Veterinary Source |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 00218812 |
| DOI: | 10.2527/jas.2016-0665 |