Title: An Analytical Study of Parallel GA with Independent Runs on GPUs
Abstract: This chapter proposes a genetic algorithm for solving QAPs with parallel independent run using GPU computation and gives a statistical analysis on how speedup can be attained with this model. With the proposed model, we achieve a GPU computation performance that is nearly proportional to the number of equipped multiprocessors (MPs) in the GPUs. We explain these computational results by performing statistical analysis. Regarding performance comparison to CPU computations, GPU computation shows a speedup of 7.2× and 13.1× on average using a single GTX 285 GPU and two GTX 285 GPUs, respectively. The parallel independent run model is the simplest of the various parallel evolutionary computation models, and among the models it demonstrates the lower limit performance.
Publication Year: 2013
Publication Date: 2013-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
Access and Citation
Cited By Count: 3
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