Combined selection of tile sizes and unroll factors using iterative compilation

2002 ◽  
Author(s):  
T. Kisuki ◽  
P.M.W. Knijnenburg ◽  
M.F.P. O'Boyle
Keyword(s):  
Iterative Compilation ◽  
Combined Selection ◽  
Selection Of

Combined selection of progeny in crop breeding using best linear unbiased prediction

2012 ◽  
Vol 92 (3) ◽  
pp. 553-562 ◽  
Author(s):  
José Marcelo Soriano Viana ◽  
Vinícius Ribeiro Faria ◽  
Fabyano Fonseca e Silva ◽  
Marcos Deon Vilela de Resende
Keyword(s):  
Least Squares ◽  
Best Linear Unbiased Prediction ◽  
Pedigree Information ◽  
Crop Breeding ◽  
Additive Variance ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Combined Selection ◽  
Selection Of ◽  
Unbiased Prediction

Viana, J. M. S., Faria, V. R., Fonseca e Silva, F. and Vilela de Resende, M. D. 2012. Combined selection of progeny in crop breeding using best linear unbiased prediction. Can. J. Plant Sci. 92: 553–562. Combined selection is an important strategy in crop breeding. As the classical index does not consider pedigree information, the objective of this study was to evaluate the efficiency of the best linear unbiased prediction (BLUP) methodology for combined selection of progeny. We analyzed expansion volume (EV) and grain yield of parents and inbred and non-inbred progeny from the popcorn population Viçosa. The BLUP analyses, single-trait and of the same character measured in parents and progeny (combined parent-family) were performed using the ASReml software. Because the experiments were balanced, the estimates of the additive variance from the BLUP and least squares analyses were generally equivalent. The accuracies of the BLUP analyses do not clearly establish the superior technique. The accuracy of the classical index tended to be higher than that obtained from BLUP analyses. There was equivalence between BLUP and least squares analyses relative to half-sib and inbred progeny selection, and superiority of the combined parent-family BLUP index for full-sib selection. The BLUP analyses also differed from the least squares analysis on the coincidence of selected parents. The populations obtained by selection based on BLUP of breeding values presented a lower effective size.

SELECTION OF SIRES ORIGINATING FROM A NUCLEUS BREEDING UNIT FOR USE IN A COMMERCIAL DAIRY POPULATION

1989 ◽  
Vol 69 (3) ◽  
pp. 595-604 ◽  
Author(s):  
GEORG TEEPKER ◽  
DAVID S. KELLER
Keyword(s):  
Embryo Transfer ◽  
Pedigree Information ◽  
Sources Of Information ◽  
Production Environment ◽  
Genetic Progress ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Commercial Population ◽  
Combined Selection ◽  
Selection Of

Bulls that originate from breeding schemes with extensive use of multiple ovulation and embryo transfer (MOET) can be selected on pedigree information, the performance of their contemporary female full- and half-sibs or based on a progeny test. Combined selection across groups of bulls with different sources of information is shown to be superior to selection of progeny tested bulls alone. The magnitude of the superiority for a given selection rate is determined by the differences in genetic merit between the groups and ranges from 5 to 65%. Depending on the annual genetic progress the majority of the bulls are selected either on pedigree or progeny information. The proportion of sib-tested bulls ranges from 9 to 23%. When breeding activities are concentrated in nucleus herds, possible genotype by environment interactions between performance in the test herd and in the commercial population have to be considered. Genotype by environment interactions increase the proportion of progeny tested sires that will be selected. However, the proportion of progeny tested sires used is reduced by genotype by environment interactions among the groups of a heterogenous commercial production environment. Key words: Embryo transfer, sire selection, genotype-by-environment interactions

scholarly journals COMBINED SELECTION OF GENOTYPES OF PIPIANA SQUASH (Cucurbita argyrosperma Huber var. stenosperma) IN THE MILPA SYSTEM

2004 ◽  
Vol X (1) ◽  
pp. 57-66
Author(s):  
Miguel Ángel Sánchez-Hernández ◽  
◽  
J.A. Mejía-Contreras ◽  
Clemente Villanueva-Verduzco ◽  
Jaime Sahagún-Castellanos ◽  
...  
Keyword(s):  
Combined Selection ◽  
Selection Of

Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

2021 ◽  
pp. 116418
Author(s):  
Philippe Bisaillon ◽  
Rimple Sandhu ◽  
Chris Pettit ◽  
Mohammad Khalil ◽  
Dominique Poirel ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Dynamic Model ◽  
Modeling Error ◽  
Combined Selection ◽  
Selection Of

Improving Program Performance via Auto-Vectorization of Loops with Conditional Statements with GCC Compiler Setting

2013 ◽  
Vol 433-435 ◽  
pp. 1410-1414
Author(s):  
Qi Shen Zhu
Keyword(s):  
Search Space ◽  
Compiler Optimizations ◽  
Program Performance ◽  
Performance Improvements ◽  
Iterative Compilation ◽  
Conditional Statements ◽  
Speed Up ◽  
Performance Ability ◽  
Number Of Passes ◽  
Selection Of

The GCC is an auto-vectorization compiler across iterations of loops to parallelism data. Turning GCC compiler optimizations flags for auto-vectorization is a way to improve the performance ability, which is a popular approach to speed up program performance. However, there are many options in GCC compiler and selecting the best combination of these options to improve program performance through vectorization is non-trivial ( as the search space is very large ).In this work we focus on the selection of compiler transformations to auto-vectorize loops with conditional statements. The selection of compiler transformations is based on the correlation between program features, speed-up, and the analysis of the code generated and a small number of passes of iterative compilation. Our preliminary experimental results show that proposed technique attains performance improvements the best ~ 6x using loops in the TSVC benchmark suite on the state-of-the-art Intel Core i3 processor.

scholarly journals Combined selection in early generation testing of self-pollinated plants

1997 ◽  
Vol 20 (4) ◽  
pp. 673-681 ◽  
Author(s):  
José Marcelo Soriano Viana ◽  
Cosme Damião Cruz
Keyword(s):  
Early Generation ◽  
Early Generation Testing ◽  
The Mean ◽  
Selection Indexes ◽  
Combined Selection ◽  
The Individual ◽  
Selection Of

Seven selection indexes based on the phenotypic value of the individual and the mean performance of its family were assessed for their application in breeding of self-pollinated plants. There is no clear superiority from one index to another although some show one or more negative aspects, such as favoring the selection of a top performing plant from an inferior family in detriment of an excellent plant from a superior family

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