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| Content Provider | Springer Nature Link |
|---|---|
| Author | Caniou, Yves Codognet, Philippe Richoux, Florian Diaz, Daniel Abreu, Salvador |
| Copyright Year | 2014 |
| Abstract | We present the parallel implementation of a constraint-based Local Search algorithm and investigate its performance on several hardware platforms with several hundreds or thousands of cores. We chose as the basis for these experiments the Adaptive Search method, an efficient sequential Local Search method for Constraint Satisfaction Problems (CSP). After preliminary experiments on some CSPLib benchmarks, we detail the modeling and solving of a hard combinatorial problem related to radar and sonar applications: the Costas Array Problem. Performance evaluation on some classical CSP benchmarks shows that speedups are very good for a few tens of cores, and good up to a few hundreds of cores. However for a hard combinatorial search problem such as the Costas Array Problem, performance evaluation of the sequential version shows results outperforming previous Local Search implementations, while the parallel version shows nearly linear speedups up to 8,192 cores. The proposed parallel scheme is simple and based on independent multi-walks with no communication between processes during search. We also investigated a cooperative multi-walk scheme where processes share simple information, but this scheme does not seem to improve performance. |
| Starting Page | 30 |
| Ending Page | 56 |
| Page Count | 27 |
| File Format | |
| ISSN | 13837133 |
| Journal | Constraints |
| Volume Number | 20 |
| Issue Number | 1 |
| e-ISSN | 15729354 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2014-07-25 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | CSP Local search Metaheuristics Parallelism Implementation Artificial Intelligence (incl. Robotics) Optimization Computing Methodologies Operations Research/Decision Theory |
| Content Type | Text |
| Resource Type | Article |
| Subject | Discrete Mathematics and Combinatorics Artificial Intelligence Computational Theory and Mathematics Software |
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