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Output details

11 - Computer Science and Informatics

Manchester Metropolitan University

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Output 19 of 37 in the submission

Article title

Enhancing data parallelism for Ant Colony Optimization on GPUs

Type

D - Journal article

DOI

10.1016/j.jpdc.2012.01.002

Title of journal

Journal of Parallel and Distributed Computing

Article number

Volume number

Issue number

First page of article

ISSN of journal

07437315

Year of publication

2013

URL

Number of additional authors

Additional information

<12>Research partially supported by EU FP7 HiPEAC project (ICT 217068), and by Spanish governmental agencies. Describes the first Graphics Processing Unit (GPU)-based parallelisation scheme for both main phases of the ant colony optimisation (ACO) algorithm, as well as a novel probabilistic selection scheme. This work has been used as the basis for ongoing Ph.D. work (Dawson & Stewart, Proc. CEC 2013), and has been cited as a foundational GPU ACO implementation (Korosec & Silc, Computational Optimization & Applications 56 (2013)).

Interdisciplinary

Cross-referral requested

Research group

A - Biological and Sensory Computation

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract