Fecha/hora: 08/06/2024 06:51:08

Biblioteca(s): | INIA Las Brujas.
Fecha corriente: | 26/11/2015
Fecha de la última actualización: | 25/11/2019
Autoria: | MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I.
Afiliación: | Y. MASUDA, Universidad de Georgia (UG); Obihiro University of Agriculture and Veterinary Medicine (Japón); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SHOGO TSURUTA, Universidad de Georgia (UG); IGNACY MISZTAL, Universidad de Georgia (UG).
Título: | Technical note: Acceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements.
Año de publicación: | 2015
Fuente/Imprenta: | Journal of Animal Science, 2015, v. 93, p. 4670 - 4674. Published October 9, 2015
DOI: | 10.2527/jas.2015-9395
Idioma: | Inglés

Notas:

Article history: Received June 8, 2015.; Accepted August 7, 2015.
1. We acknowledge the work by François Guillaume in programming a hash function. We greatly appreciate the work of the two anonymous reviewers.
2. The AIREMLF90 program with a sparse package YAMS, along with a manual, is available at http://nce.ads.uga.edu. The YAMS package is available on request for academic or noncommercial purposes by contacting the corresponding author.

Contenido:

ABSTRACT.

The objective of this study was to remove bottlenecks generally found in a computer program for average-information REML. The refinements included improvements to setting-up mixed-model equations on a hash table with a faster hash function as sparse matrix storage, changing sparse structures in calculation of traces, and replacing a sparse matrix
package using traditional methods (FSPAK) with a new package using supernodal methods (YAMS); the latter package quickly processed sparse matrices containing large, dense blocks. Comparisons included 23 models with data sets from broiler, swine, beef, and dairy cattle. Models included single-trait, multiple-trait, maternal, and random regression models with phenotypic data; selected models used genomic information in a singlestep approach. Setting-up mixed model equations was completed without abnormal termination in all analyses. Calculations in traces were accelerated with a hash format, especially for models with a genomic relationship matrix, and the maximum speed was 67 times faster. Computations with YAMS were, on average, more than 10 times faster than with FSPAK and had greater advantages for large data and more complicated models including multiple traits, random regressions, and genomic effects. These refinements can be applied to general average-information REML programs.

© 2015 American Society of Animal Science. All rights reserved.

Palabras-Clave: | AVERAGE-INFORMATION REML; HASH FORMAT; SPARSE MATRIX; SPARSE PACKAGES.
Thesagro: | MODELOS DE SIMULACIÓN.
Categoría del tema: | L10 Genética y mejoramiento animal
Registro original: | INIA Las Brujas (LB)
Ejemplares: | LB - (100870-1) - PXI - AP - DD - PP/Journal of Animal Science/2015 -  -  - DIS