GENETIC ALGORITHM ON GENERAL PURPOSE GRAPHICS PROCESSING UNIT: PARALLELISM REVIEW

Autor:	A.J. Umbarkar, M.S. Joshi, N.M. Rothe
Jazyk:	angličtina
Rok vydání:	2013
Předmět:	Genetic Algorithm (GA) Parallel Genetic Algorithm (PGA) General Purpose Graphics Processing Unit (GPGPU) Compute Unified Device Architecture (CUDA) Open Computing Language (OpenCL) Computer engineering. Computer hardware TK7885-7895
Zdroj:	ICTACT Journal on Soft Computing, Vol 3, Iss 2, Pp 492-497 (2013)
Druh dokumentu:	article
ISSN:	0976-6561 2229-6956
Popis:	Genetic Algorithm (GA) is effective and robust method for solving many optimization problems. However, it may take more runs (iterations) and time to get optimal solution. The execution time to find the optimal solution also depends upon the niching-technique applied to evolving population. This paper provides the information about how various authors, researchers, scientists have implemented GA on GPGPU (General purpose Graphics Processing Units) with and without parallelism. Many problems have been solved on GPGPU using GA. GA is easy to parallelize because of its SIMD nature and therefore can be implemented well on GPGPU. Thus, speedup can definitely be achieved if bottleneck in GAs are identified and implemented effectively on GPGPU. Paper gives review of various applications solved using GAs on GPGPU with the future scope in the area of optimization.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/c2a3c5399fc544dcb13f392aeaa36702 Zobrazit plný text záznamu View record in DOAJ