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Review on different Meta-Heuristic Techniques for Parallel Computing

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Davinderjit Kaur, Amit Chabbra
10.5120/ijca2017914599

Davinderjit Kaur and Amit Chabbra. Review on different Meta-Heuristic Techniques for Parallel Computing. International Journal of Computer Applications 169(2):15-19, July 2017. BibTeX

@article{10.5120/ijca2017914599,
	author = {Davinderjit Kaur and Amit Chabbra},
	title = {Review on different Meta-Heuristic Techniques for Parallel Computing},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {169},
	number = {2},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {15-19},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume169/number2/27957-2017914599},
	doi = {10.5120/ijca2017914599},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This paper represents the parallel computing  is a type of working out through which many data or the execution connected with processes are finished concurrently as well as scheduling along with source of information permitting so that we can optimize efficiency standards within multi-cluster heterogeneous situations is acknowledged for NP-hard problems. Multi-cluster environments are commonly represented as a substitution to high-performance computing regarding resolving large-scale search engine optimization difficulties. The review has shown the various meta heuristic techniques which has proved their usefulness to find the optimum schedule around large-scale allocated circumstances. It also shows the comparison of Meta heuristic techniques which evaluates the real workload trace as well as shows the advantages and disadvantages when it comes to other well-known approaches outlined inside literature.

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Keywords

Parallel computing, multi-clusters, co-allocation, meta-heuristics