Output details
11 - Computer Science and Informatics
Manchester Metropolitan University
Article title
Enhancing data parallelism for Ant Colony Optimization on GPUs
Type
D - Journal article
Title of journal
Journal of Parallel and Distributed Computing
Article number
-
Volume number
73
Issue number
1
First page of article
42
ISSN of journal
07437315
Year of publication
2013
URL
-
Number of additional authors
3
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
3
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-