research-article

A Compile-Time Scheduling Heuristic for Interconnection-Constrained Heterogeneous Processor Architectures

Authors:

E. A. LeeAuthors Info & Claims

IEEE Transactions on Parallel and Distributed Systems, Volume 4, Issue 2

Pages 175 - 187

https://doi.org/10.1109/71.207593

Published: 01 February 1993 Publication History

Abstract

The authors present a compile-time scheduling heuristic called dynamic level scheduling,which accounts for interprocessor communication overhead when mappingprecedence-constrained, communicating tasks onto heterogeneous processorarchitectures with limited or possibly irregular interconnection structures. This techniqueuses dynamically-changing priorities to match tasks with processors at each step, andschedules over both spatial and temporal dimensions to eliminate shared resourcecontention. This method is fast, flexible, widely targetable, and displays promisingperformance.

References

[1]

{1} S. F. Nugent, "The iPSC/s direct-connect communications technology," in Proc. Third Conf. Hypercube Concurrent Comput. and Appl., vol. 1, Jan. 1988.

[2]

{2} S. Borkar et al., "iWarp: An integrated solution to high-speed parallel computing," Carnegie Mellon Tech. Rep. CMU-CS-89-104, pp. 1-10, Jan. 1989.

[3]

{3} E. A. Lee and D. G. Messerschmitt, "Static scheduling of synchronous data flow programs for digital signal processing," IEEE Trans. Comput., vol. C-36, no. 2, Jan. 1987.

[4]

{4} E. A. Lee and S. Ha, "Scheduling strategies for multiprocessor real-time DSP," in Proc. Globecom, Nov. 1989.

[5]

{5} V. Sarkar, Partitioning and Scheduling Parallel Programs for Multiprocessors . Cambridge, MA: M.I.T. Press, 1989.

Digital Library

[6]

{6} W. W. Chu, L. J. Holloway, M. T. Lan, and K. Efe, "Task allocation in distributed data processing," IEEE Comput. Mag., pp. 57-69, Nov. 1980.

Digital Library

[7]

{7} W. W. Chu and L. M. T. Lan, "Task allocation and precedence relations for distributed real-time systems," IEEE Trans. Comput., vol. C-36, no. 6, pp. 667-679, June 1987.

[8]

{8} S. W. Bollinger and S. F. Midkiff, "Processor and link assignment in multicomputers using simulated annealing," in 1988 ICPP Proc., vol. 1, Aug. 1988, pp. 1-7.

[9]

{9} K. Efe. "Heuristic models of task assignment scheduling in distributed systems," IEEE Comput. Mag., pp. 50-56, June 1982.

Digital Library

[10]

{10} H. S. Stone, "Multiprocessor scheduling with the aid of network flow algorithms," IEEE Trans. Software Eng., vol. SE-3, no. 1, pp. 85-93, Jan, 1977.

Digital Library

[11]

{11} S.J. Kim and J. C. Browne. "A general approach to mapping of parallel computations upon multiprocessor architectures," in 1988 ICPP Proc., vol. 3, Aug. 1988, pp. 1-8.

[12]

{12} J. C. Bier, E. E Goei, W. H. Ho, P. D. Lapsley, M. P. O'Reilly, G. C. Sih, and E. A. Lee, "Gabriel: A design environment for DSP," IEEE Micro Mag., Oct. 1990.

[13]

{13} R. P. Bianchini Jr. and J. P. Shen, "Interprocessor traffic scheduling algorithm for multiple-processor networks," IEEE Trans. Comput., vol. C-36, no. 4, pp. 396-409, Apr. 1987.

[14]

{14} T.C. Hu, "Parallel sequencing and assembly line problems," Oper. Res., vol. 9, no. 6, pp. 841-848, Nov. 1961.

Digital Library

[15]

{15} T. L. Adam, K. M. Chandy, and J. R. Dickson, "A comparison of list schedules for parallel processing systems," Commun. ACM, vol. 17, no. 12, pp. 685-690, Dec. 1974.

Digital Library

[16]

{16} W. H. Kohler, "A preliminary evaluation of the critical path method for scheduling tasks on multiprocessor systems," IEEE Trans. Comput., pp. 1235-1238, Dec. 1975.

Digital Library

[17]

{17} W. H. Yu, "LU decomposition on a multiprocessing system with communication delay," Ph.D. dissertation, U.C. Berkeley, 1984.

[18]

{18} G, C. Sih and E. A. Lee, "A multiprocessor scheduling strategy," UCB/ERL Memo, M90/119, pp. 1-34, Dec. 1990.

Cited By

Li HChen BHuang JCañizares Abreu JChai SXia Y(2024)Mutation-driven and population grouping PRO algorithm for scheduling budget-constrained workflows in the cloudCluster Computing10.1007/s10586-023-04006-w27:1(1137-1158)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10586-023-04006-w
Alam MShahid MMustajab S(2024)Security prioritized multiple workflow allocation model under precedence constraints in cloud computing environmentCluster Computing10.1007/s10586-022-03819-527:1(341-376)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10586-022-03819-5
Zhadan AAllahverdyan AKondratov IMikheev VPetrosian ORomanovskii AKharin V(2023)Multi-agent Reinforcement Learning-based Adaptive Heterogeneous DAG SchedulingACM Transactions on Intelligent Systems and Technology10.1145/361030014:5(1-26)Online publication date: 3-Oct-2023
https://dl.acm.org/doi/10.1145/3610300
Show More Cited By

Recommendations

Dynamic-level scheduling for heterogeneous processor networks
SPDP '90: Proceedings of the 1990 IEEE Second Symposium on Parallel and Distributed Processing

Dynamic-level scheduling is an effective compile-time scheduling technique which accounts for interprocessor communication overhead when mapping precedence-constrained, communicating tasks onto arbitrarily interconnected processor networks. Scheduling ...
Scheduling of deteriorating jobs with release dates to minimize the maximum lateness

In this paper, we consider the problem of scheduling n deteriorating jobs with release dates on a single (batching) machine. Each job's processing time is a simple linear function of its starting time. The objective is to minimize the maximum lateness. ...
Analysis of Macro-Dataflow Dynamic Scheduling on Nonuniform Memory Access Architectures

The author studies dynamic scheduling of computational tasks with communication costsusing nonuniform memory access architecture. The computing model assumes that datatransfer can be partitioned into parallel and sequential parts with respect to the ...

Comments

Information & Contributors

Information

Published In

cover image IEEE Transactions on Parallel and Distributed Systems

IEEE Transactions on Parallel and Distributed Systems Volume 4, Issue 2

February 1993

120 pages

ISSN:1045-9219

Issue’s Table of Contents

Copyright © Copyright © 1993 IEEE. All Rights Reserved.

Publisher

IEEE Press

Publication History

Published: 01 February 1993

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

247
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 11 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

Li HChen BHuang JCañizares Abreu JChai SXia Y(2024)Mutation-driven and population grouping PRO algorithm for scheduling budget-constrained workflows in the cloudCluster Computing10.1007/s10586-023-04006-w27:1(1137-1158)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10586-023-04006-w
Alam MShahid MMustajab S(2024)Security prioritized multiple workflow allocation model under precedence constraints in cloud computing environmentCluster Computing10.1007/s10586-022-03819-527:1(341-376)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10586-022-03819-5
Zhadan AAllahverdyan AKondratov IMikheev VPetrosian ORomanovskii AKharin V(2023)Multi-agent Reinforcement Learning-based Adaptive Heterogeneous DAG SchedulingACM Transactions on Intelligent Systems and Technology10.1145/361030014:5(1-26)Online publication date: 3-Oct-2023
https://dl.acm.org/doi/10.1145/3610300
Senapati DSarkar AKarfa C(2023)Energy-Aware Real-Time Scheduling of Multiple Periodic DAGs on Heterogeneous SystemsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.322850442:8(2447-2460)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1109/TCAD.2022.3228504
Chen YLiu SChen YLing X(2023)A scheduling algorithm for heterogeneous computing systems by edge cover queueKnowledge-Based Systems10.1016/j.knosys.2023.110369265:COnline publication date: 8-Apr-2023
https://dl.acm.org/doi/10.1016/j.knosys.2023.110369
Sukhoroslov OGorokhovskii M(2023)Benchmarking DAG Scheduling Algorithms on Scientific Workflow InstancesSupercomputing10.1007/978-3-031-49435-2_1(3-20)Online publication date: 25-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-49435-2_1
Sukhoroslov O(2023)Scheduling of Workflows with Task Resource Requirements in Cluster EnvironmentsParallel Computing Technologies10.1007/978-3-031-41673-6_14(177-196)Online publication date: 21-Aug-2023
https://dl.acm.org/doi/10.1007/978-3-031-41673-6_14
Gupta PBhagat SRawat P(2022)Fault aware hybrid harmony search technique for optimal resource allocation in cloudJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-21184642:4(3677-3689)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/JIFS-211846
Wang ZDuan HCheng Y(2022)An Improving List Scheduling Algorithm Based on Reinforcement Learning and Task DuplicationProceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence10.1145/3579654.3579657(1-7)Online publication date: 23-Dec-2022
https://dl.acm.org/doi/10.1145/3579654.3579657
Senapati DSarkar AKarfa C(2022)PRESTO: A Penalty-Aware Real-Time Scheduler for Task Graphs on Heterogeneous PlatformsIEEE Transactions on Computers10.1109/TC.2021.305238971:2(421-435)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1109/TC.2021.3052389
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents