Genetic algorithm based DSP multiprocessor scheduling

RW Amphlett, DR Bull

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)
352 Downloads (Pure)


This paper presents recent work on the application of genetic algorithms to the NP-complete problem of multiprocessor scheduling for audio DSP algorithms. The genetic algorithm is used to schedule algorithms written in the form of data flow graphs onto specified multiprocessor arrays. A unique chromosome representation technique is described and a number of application-specific genetic operators are introduced. Comparisons of the performance of the genetic algorithm technique with heuristic scheduling techniques show that the choice of the most suitable technique varies with the structure and complexity of the scheduling problem. Finally, techniques for combining heuristic and genetic algorithm scheduling techniques are discussed
Translated title of the contributionGenetic algorithm based DSP multiprocessor scheduling
Original languageEnglish
Title of host publicationUnknown
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages253 - 256
ISBN (Print)078030730, 0780330730
Publication statusPublished - May 1996
EventInternational Symposium on Circuits and Systems - Atlanta, United States
Duration: 1 May 1996 → …


ConferenceInternational Symposium on Circuits and Systems
Country/TerritoryUnited States
Period1/05/96 → …

Bibliographical note

Conference Proceedings/Title of Journal: IEEE international symposium on circuits and systems
Other: Ch.201
Rose publication type: Conference contribution

Sponsorship: The authors gratefully acknowledge the support of Sony Broadcast and Professional Europe and The Centre for Communications Research, University of Bristol.

Terms of use: Copyright © 1996 IEEE. Reprinted from IEEE International Symposium on Circuits and Systems, 1996 (ISCAS '96).

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to

By choosing to view this document, you agree to all provisions of the copyright laws protecting it.


Dive into the research topics of 'Genetic algorithm based DSP multiprocessor scheduling'. Together they form a unique fingerprint.

Cite this