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A Genetic Task Migration Algorithm for Fault Recovery in NoC-based Manycore Systems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Wang, Jinxiang Zixu, Wu Fang-Fa, Fu |
| Copyright Year | 2015 |
| Abstract | Recovery from permanent core faults in NoC-based manycore systems usually requires migrating tasks from faulty cores to fault-free cores, where balanced workloads are commonly desired. Finding optimal migration destinations for tasks, however, is a challenging issue due to the time complexity of the search process. To cope with this, in this paper, a genetic algorithm based task migration algorithm is proposed, where the adaptive crossover (AC) scheme and the An chaotic mapping disturbance (AD) scheme are incorporated to improve the search efficiency. Experiments show that the modifications to the standard genetic algorithm (SGA) are effective, and the proposed task migration algorithm outperforms two PSO-based algorithms, the SGA and a deterministic algorithm (DA) in finding more balanced migration solutions. The average improvements of the proposed algorithm over the DA, PSO, DPSO, and SGA algorithms are 86%, 88%, 37%, and 16%, respectively. Key-Words: Task migration, genetic algorithm, fault recovery, NoC, manycore system |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.wseas.org/multimedia/journals/computers/2015/a985705-677.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
