Particle Swarm Optimization for Constrained Instruction Scheduling
Author
Source
Issue
Vol. 2008, Issue 2008 (31 Dec. 2008), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-03-15
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Engineering Sciences and Information Technology
Abstract EN
Instruction scheduling is an optimization phase aimed at balancing the performance-cost tradeoffs of the design of digital systems.
In this paper, a formal framework is tailored in particular to find an optimal solution to the resource-constrained instruction scheduling problem in high-level synthesis.
The scheduling problem is formulated as a discrete optimization problem and an efficient population-based search technique; particle swarm optimization (PSO) is incorporated for efficient pruning of the solution space.
As PSO has proven to be successful in many applications in continuous optimization problems, the main contribution of this paper is to propose a new hybrid algorithm that combines PSO with the traditional list scheduling algorithm to solve the discrete problem of instruction scheduling.
The performance of the proposed algorithms is evaluated on a set of HLS benchmarks, and the experimental results demonstrate that the proposed algorithm outperforms other scheduling metaheuristics and is a promising alternative for obtaining near optimal solutions to NP-complete scheduling problem instances.
American Psychological Association (APA)
Abdel-Kader, Rehab F.. 2009. Particle Swarm Optimization for Constrained Instruction Scheduling. VLSI Design،Vol. 2008, no. 2008, pp.1-7.
https://search.emarefa.net/detail/BIM-509084
Modern Language Association (MLA)
Abdel-Kader, Rehab F.. Particle Swarm Optimization for Constrained Instruction Scheduling. VLSI Design No. 2008 (2008), pp.1-7.
https://search.emarefa.net/detail/BIM-509084
American Medical Association (AMA)
Abdel-Kader, Rehab F.. Particle Swarm Optimization for Constrained Instruction Scheduling. VLSI Design. 2009. Vol. 2008, no. 2008, pp.1-7.
https://search.emarefa.net/detail/BIM-509084
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-509084