DocumentCode
262136
Title
NSGA-II: Implementation and Performance Metrics Extraction for CPU and GPU
Author
Padurariu, Florina Roxana ; Marinescu, Cristina
Author_Institution
”Politeh.“ Univ. Timisoara, Timisoara, Romania
fYear
2014
fDate
22-25 Sept. 2014
Firstpage
494
Lastpage
499
Abstract
Multi-objective Optimization Evolutionary Algorithms are widely employed for solving different real-world optimization problems. Usually their runs involve a considerable amount of time because of the need to evaluate many functions. This particularity makes them good candidates of parallelization. In this work we investigate the benefits of the GPU implementation of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) versus its CPU implementation in terms of the execution time.
Keywords
genetic algorithms; graphics processing units; CPU; GPU; NSGA-II; evolutionary algorithms; multiobjective optimization; non-dominated sorting genetic algorithm II; performance metrics extraction; Convergence; Graphics processing units; Linear programming; Optimization; Sociology; Sorting; Statistics; CPU; GPU; empirical software engineering; multi-objective evolutionary algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2014 16th International Symposium on
Conference_Location
Timisoara
Print_ISBN
978-1-4799-8447-3
Type
conf
DOI
10.1109/SYNASC.2014.72
Filename
7034722
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