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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
31/03/2021 |
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Actualizado : |
31/03/2021 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. |
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Afiliación : |
YATUKA MASUDA, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SHOGO TSURUTA; IGNACY MISZTAL, University of Georgia, Athens, USA. |
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Título : |
Acceleration of computations in AI REML for single-step GBLUP models. |
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Complemento del título : |
Volume Methods and Tools: Statistical methods - linear and nonlinear models (Posters), 703. |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.703. |
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Idioma : |
Inglés |
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Contenido : |
ABSTRACT.
The objective of this study was to evaluate the advantage of the YAMS package over the FSPAK package in average-information (AI) REML for single-step GBLUP models. Data sets from broiler and Holsteins were used in this study. (Co)variance components were estimated with the AIREMLF90 program which could switch YAMS and FSPAK for sparse operations. The YAMS package used the BLAS and LAPACK libraries using all the 16 cores on CPU. For a single-trait model applied to the data contained over 15,000 genotyped animals, FSPAK took over 4 hours to finish the first 5 rounds while YAMS took 20 minutes. For a 4-trait model applied to the same data set, FSPAK failed in the sparse factorization while YAMS took 5 hours to finish the first 5 rounds. The use of YAMS can dramatically increase speed and stability of AIREMLF90 for single-step GBLUP models. |
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Palabras claves : |
Single step GBLUP; Supernodal methods; Variance component estimation. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15447/1/Masuda-et-al.-2014.-WCGALP.pdf
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Marc : |
LEADER 01492nam a2200181 a 4500
001 1061923
005 2021-03-31
008 2014 bl uuuu u01u1 u #d
100 1 $aMASUDA, Y.
245 $aAcceleration of computations in AI REML for single-step GBLUP models.$h[electronic resource]
260 $aIn: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.703.$c2014
520 $aABSTRACT. The objective of this study was to evaluate the advantage of the YAMS package over the FSPAK package in average-information (AI) REML for single-step GBLUP models. Data sets from broiler and Holsteins were used in this study. (Co)variance components were estimated with the AIREMLF90 program which could switch YAMS and FSPAK for sparse operations. The YAMS package used the BLAS and LAPACK libraries using all the 16 cores on CPU. For a single-trait model applied to the data contained over 15,000 genotyped animals, FSPAK took over 4 hours to finish the first 5 rounds while YAMS took 20 minutes. For a 4-trait model applied to the same data set, FSPAK failed in the sparse factorization while YAMS took 5 hours to finish the first 5 rounds. The use of YAMS can dramatically increase speed and stability of AIREMLF90 for single-step GBLUP models.
653 $aSingle step GBLUP
653 $aSupernodal methods
653 $aVariance component estimation
700 1 $aAGUILAR, I.
700 1 $aTSURUTA, S.
700 1 $aMISZTAL, I.
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INIA Las Brujas (LB) |
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| Registros recuperados : 81 | |
| 14. |  | LEGARRA, A.; AGUILAR, I.; MISZTAL, I. Single step methods with a view towards poultry breeding. Volume Species Breeding: Poultry, 324. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.324. Acknowledgements: This work has been financed by X-Gen and GenSSeq actions from SelGen metaprogram (INRA).| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 17. | | MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. Acceleration of computations in AI REML for single-step GBLUP models. Volume Methods and Tools: Statistical methods - linear and nonlinear models (Posters), 703. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.703.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 19. | | BERMANN, M.; MISZTAL, I.; LOURENCO, D.; AGUILAR, I.; LEGARRA, A. Definition of reliabilities for models with metafounders. [289] Part 17 - Challenges - improving genomic prediction. In: Proceedings of the World Congress on Genetics Applied to Livestock Production (WCGALP), 12., Rotterdam, the Netherlands, 3-8 July 2022. doi: https://doi.org/10.3920/978-90-8686-940-4_289 1217-1220. Article history: Published online: February 9, 2023. -- Corresponding author: A. Legarra, email: andres.legarra@inrae.fr -- Acknowledgment: This work received financing from European Unions' Horizon 2020 Research & Innovation Programme,...| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 81 | |
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