NDLI: Influence of parallel metrics in the analysis of parallel metaheuristic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Garcia, A. Luque, G. Alba, E.
Copyright Year	2011
Description	Author affiliation: Departamento de IGSW, Facultad 1, Universidad de las Ciencias Informáticas, La Habana, Cuba (Garcia, A.) \|\| Depto. de Lenguajes y Ciencias, de La Computatión, Universidad de Málaga, Málaga, España (Luque, G.; Alba, E.)
Abstract	High computational requirements of current problems have driven most researches towards efficient processing formulations which require the use of multiple processors interconnected, this is the foundation of the parallel processing mechanism. Among the metrics to measure the performance of parallel algorithms, the most important and used is the speedup, but in the scientific community does not exist a consent on its definition and use. The aim of this work is to study different alternatives evaluating parallel metaheuristics. This report presents the results of several experimental tests to show the use of the speedup evaluating the same parallel distributed Genetic Algorithm in different ways, to solve MAXSAT problem. Our experiments show that depending on how the algorithm speedup is evaluated, different results can be obtained. Taking into account the test results we can conclude that the best scenario for evaluating parallel algorithms is comparing algorithms with the same accuracy, defining the quality of the solutions as stop condition, because all executions reach the optimal value allowing fair comparisons.
Starting Page	748
Ending Page	753
File Size	260248
Page Count	6
File Format	PDF
ISBN	9781457716768
ISSN	21647151
e-ISBN	9781457716768
DOI	10.1109/ISDA.2011.6121746
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-22
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Algorithm design and analysis Program processors Accuracy metric speedup distributed genetic algorithm Parallel algorithms Intelligent systems parallel metaheuristics Genetic algorithms
Content Type	Text
Resource Type	Article

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