article

Free access

Automatic determination of grain size for efficient parallel processing

Authors:

Carolyn McCreary,

Helen GillAuthors Info & Claims

Communications of the ACM, Volume 32, Issue 9

Pages 1073 - 1078

https://doi.org/10.1145/66451.66454

Published: 01 September 1989 Publication History

PDF eReader

Abstract

The authors propose a method for automatic determination and scheduling of modules from a sequential program.

References

[1]

Babb, R. Parallel processing with large-grain data flow techniques. IEEE Comput. (July 1984J, 55-61.

Digital Library

Google Scholar

[2]

Ehrenfeucht, A., and Rosenberg, G. A decomposition theorem for -structures. Technica{ Report No. CU-CS-328-86. University of Colorado, Boulder, 1986.

Google Scholar

[3]

Kruatrachue, B., and Lewis, T. Grain size determination for parallel processing. IEEE Sofiw. (Jan. 1988), 23-32.

Digital Library

Google Scholar

[4]

Kuck, D. The structure of an advanced vectorizer for pipelined proc~:ssors. In Proceedings of COMPSAC {October 1980), pp. 709-715.

Google Scholar

[5]

Leiserson, C., and Maggs, B. Communication-e~ficient parallel graph algorithms. International Parallel Processing Conference, IEEE, 1986.

Google Scholar

[6]

McCreary, C. An algorithm for parsing a graph grammar. Ph.D. dissertation, University of Colorado, Boulder, April 1987.

Digital Library

Google Scholar

[7]

Saltz, J. Automated problem scheduling and reduction of synchronization delay effects. ICASE Report No. 87-22. NASA Institute for Computer Applications in Science and Engineering, July 1987.

Google Scholar

Cited By

View all

Boveiri HJavidan RKhayami R(2020)An intelligent hybrid approach for task scheduling in cluster computing environments as an infrastructure for biomedical applicationsExpert Systems10.1111/exsy.1253638:1Online publication date: 12-Feb-2020
https://doi.org/10.1111/exsy.12536
Boveiri HElhoseny M(2020)RETRACTED ARTICLE: A-COA: an adaptive cuckoo optimization algorithm for continuous and combinatorial optimizationNeural Computing and Applications10.1007/s00521-018-3928-932:3(681-705)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s00521-018-3928-9
Boveiri H(2020)An enhanced cuckoo optimization algorithm for task graph scheduling in cluster-computing systemsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-04520-324:13(10075-10093)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1007/s00500-019-04520-3
Show More Cited By

Index Terms

Automatic determination of grain size for efficient parallel processing

Recommendations

Automatic Coarse Grain Task Parallel Processing on SMP Using OpenMP
LCPC '00: Proceedings of the 13th International Workshop on Languages and Compilers for Parallel Computing-Revised Papers

This paper proposes a simple and efficient implementation method for a hierarchical coarse grain task parallel processing scheme on a SMP machine. OSCAR multigrain parallelizing compiler automatically generates parallelized code including OpenMP ...
Grain Size Determination for Parallel Processing

A method called grain packing is proposed as a way to optimize parallel programs. A grain is defined as one or more concurrently executing program modules. A grain begins executing as soon as all of its inputs are available, and terminates only after ...
Coarse-Grain Task Parallel Processing Using the OpenMP Backend of the OSCAR Multigrain Parallelizing Compiler
ISHPC '00: Proceedings of the Third International Symposium on High Performance Computing

This paper describes automatic coarse grain parallel processing on a shared memory multiprocessor system using a newly developed OpenMP backend of OSCAR multigrain parallelizing compiler for from single chip multiprocessor to a high performance ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

Communications of the ACM Volume 32, Issue 9

Special issue: multiprocessing

Sept. 1989

93 pages

ISSN:0001-0782

EISSN:1557-7317

DOI:10.1145/66451

Editor:
Peter J. Denning
NASA Ames Research Center, Moffett Field, CA

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 1989

Published in CACM Volume 32, Issue 9

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

92
Total Citations
View Citations
724
Total Downloads

Downloads (Last 12 months)121
Downloads (Last 6 weeks)10

Reflects downloads up to 18 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Boveiri HJavidan RKhayami R(2020)An intelligent hybrid approach for task scheduling in cluster computing environments as an infrastructure for biomedical applicationsExpert Systems10.1111/exsy.1253638:1Online publication date: 12-Feb-2020
https://doi.org/10.1111/exsy.12536
Boveiri HElhoseny M(2020)RETRACTED ARTICLE: A-COA: an adaptive cuckoo optimization algorithm for continuous and combinatorial optimizationNeural Computing and Applications10.1007/s00521-018-3928-932:3(681-705)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s00521-018-3928-9
Boveiri H(2020)An enhanced cuckoo optimization algorithm for task graph scheduling in cluster-computing systemsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-04520-324:13(10075-10093)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1007/s00500-019-04520-3
Boveiri H(2019)Supercomputing with an Efficient Task Scheduler as an Infrastructure for Big Multimedia ProcessingHandbook of Multimedia Information Security: Techniques and Applications10.1007/978-3-030-15887-3_35(723-752)Online publication date: 20-Jul-2019
https://doi.org/10.1007/978-3-030-15887-3_35
Wang HSinnen O(2018)List-Scheduling versus Cluster-SchedulingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2018.280895929:8(1736-1749)Online publication date: 1-Aug-2018
https://doi.org/10.1109/TPDS.2018.2808959
Boveiri HKhayami RElhoseny MGunasekaran M(2018)An efficient Swarm-Intelligence approach for task scheduling in cloud-based internet of things applicationsJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-018-1071-110:9(3469-3479)Online publication date: 4-Oct-2018
https://doi.org/10.1007/s12652-018-1071-1
Mallach S(2018)Improved mixed-integer programming models for the multiprocessor scheduling problem with communication delaysJournal of Combinatorial Optimization10.1007/s10878-017-0199-936:3(871-895)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1007/s10878-017-0199-9
Boveiri H(2017)An incremental ant colony optimization based approach to task assignment to processors for multiprocessor schedulingFrontiers of Information Technology & Electronic Engineering10.1631/FITEE.150039418:4(498-510)Online publication date: 19-Apr-2017
https://doi.org/10.1631/FITEE.1500394
Boveiri H(2016)A Novel ACO-Based Static Task Scheduling Approach for Multiprocessor EnvironmentsInternational Journal of Computational Intelligence Systems10.1080/18756891.2016.12371819:5(800)Online publication date: 2016
https://doi.org/10.1080/18756891.2016.1237181
Chaudhary NAlGhamdi MAnjum APapadopoulos G(2015)Scheduling workflows under authorization controlProceedings of the 8th International Conference on Utility and Cloud Computing10.5555/3233397.3233512(583-588)Online publication date: 7-Dec-2015
https://dl.acm.org/doi/10.5555/3233397.3233512
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Abstract

References

Cited By

Index Terms

Recommendations

Automatic Coarse Grain Task Parallel Processing on SMP Using OpenMP

Grain Size Determination for Parallel Processing

Coarse-Grain Task Parallel Processing Using the OpenMP Backend of the OSCAR Multigrain Parallelizing Compiler

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

PDF

eReader

Login options

Full Access

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations