Abstract
Heterogeneous computing environments have become attractive platforms to schedule computationally intensive jobs. We consider the problem of mapping independent tasks onto machines in a heterogeneous environment where expected execution time of each task on each machine is known. Although this problem has been much studied in the past, we derive new insights into the effectiveness of different mapping heuristics by use of two metrics - efficacy (E) and utilization (U). Whereas there is no consistent rank ordering of the various previously proposed mapping heuristics on the basis of total task completion time, we find a very consistent rank ordering of the mapping schemes with respect to the new metrics. Minimization of total completion time requires maximization of the product EĆU. Using the insights provided by the metrics, we develop a new matching heuristic that produces high-quality mappings using much less time than the most effective previously proposed schemes.
This work was supported in part by a grant from the Ohio Board of Regents.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
A.H. Alhusaini, V. K. Prasanna, and C. S. Raghavendra. A Unified Resource Scheduling Framework for Heterogeneous Computing Environments, 8th Heterogeneous Computing Workshop (HCWā 99), Apr. 1999
R. Armstrong, D. Hensgen, and T. Kidd. The Relative Performance of Various Mapping Algorithms is Independent of Sizable Variances in Run-time Predictions, 7th IEEE Heterogeneous Computing Workshop (HCWā98), Mar. 1998, pp.79ā87
B. Armstrong, R. Eigenmann. Performance Forecasting: Towards a Methodology for Characterizing Large Computational Applications. Proceedings of the 1998 International Conference on Parallel Processing, Aug. 1998, pp. 518ā527
F. Berman, R. Wolski, S. Figueira, J. Schopf, and G. Shao. Aplication-Level Scheduling on Distributed Heterogeneous Networks, Proceedings of Supercomputing 1996
F. Berman and R. Wolski. Scheduling from the Perspective of the Application, from Proceedings of Symposium on High Performance Distributed Computing, 1996
T. D. Braun, H. J. Siegel, N. Beck, L. L. Bƶlƶni, M. Maheswaran, A. I. Reuther, J. R. Robertson, M. D. Theys, Bin Yao, D. Hensgen, and R. F. Freund. A Comparison Study of Static Mapping Heuristics for a Class of Meta-tasks on Heterogeneous Computing Systems, 8th IEEE Heterogeneous Computing Workshop (HCWā99), Apr. 1999, pp.15ā29
T.D. Braun, H.J. Siegel, N. Beck, L.L. Bƶlƶni, M. Maheswaran, A.I. Reuther, J.P. Robertson, M.D. Theys, and B. Yao. A Taxonomy for Describing Matching and Scheduling Heuristics for Mixed-machine Heterogeneous Computing Systems, IEEE Workshop on Advances in Parallel and Distributed Systems, Oct. 1998, pp. 330ā335
F. Chang, V. Karamcheti, Z. Kedem. Exploiting Application Tunability for Efficient, Predictable Parallel Resource Management. Proceedings of the 13th International Parallel Processing Symposium / Symposium 10th Symposium on Parallel and Distributed Processing, Apr. 1999, pp.749ā758
D. Feitelson, A. Weil. Utilization and Predictability in Scheduling the IBM SP/2 with Backfilling. Proceedings of the 12th International Parallel Processing / Symposium 9th Symposium on Parallel and Distributed Processing, Apr. 1998, pp. 542ā548
I. Foster and C. Kesselman. The Grid: Blueprint for a New Computing Infrastructure, Morgan Kaufmann Publishers, 1998
P. Holenarsipur, V. Yarmolenko, J. Duato, D.K. Panda, and P. Sadayappan, āCharacterization and Enhancement of Static Mapping Heuristics for Heterogeneous Systems,ā Technical report OSU-CISRC-2/00-TR07, Department of Computer and Information Science, Ohio State University, 2000
O. H. Ibarra and C. E. Kim. Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors. Journal of the ACM, Vol.24, No.1, Jan. 1977, pp. 280ā289
M. Kafil and I. Ahmad. Optimal Task Assignment in Heterogeneous Computing Systems. 6th IEEE Heterogeneous Computing Workshop (HCWā97), Apr. 1997, pp. 135ā146
W. Leinberger, G. Karypis, and V. Kumar. Multi-Capacity Bin Packing Algorithms with Applications to Job Scheduling under Multiple Constraints. Proceedings of the 1999 International Conference on Parallel Processing, Aug. 1999, pp. 404ā413
M. Maheswaran, Shoukat Ali, H. J. Siegel, D. Hensgen, and R. F. Freund. Dynamic Matching and Scheduling of a Class of Independent Tasks onto Heterogeneous Computing Systems. 8th IEEE Heterogeneous Computing Workshop (HCWā99), Apr. 1999, pp. 30ā44
A. Radulescu and A. van Gemund. FLB: Fast Load Balancing for Distributed-Memory Machines. Proceedings of the 1999 International Conference on Parallel Processing, Aug. 1999, pp. 534ā542
J. Schopf, F. Berman. Performance Prediction in Production Environments. Proceedings of the 12th International Parallel Processing/Symposium 9th Symposium on Parallel and Distributed Processing, Apr. 1998, pp. 647ā654
G. Shao, R. Wolski and F. Berman. Performance Effects of Scheduling Strategies for Master/Slave Distributed Applications. UCSD Technical Report No. CS98-598
H. Singh and A. Youssef, Mapping and Scheduling Heterogeneous Task Graphs using Genetic Algorithms. 5th IEEE Heterogeneous Computing Workshop (HCWā96), Apr. 1996
H. Topcuoglu, S. Hariri, and Min-You Wu. Task Scheduling Algorithms for Heterogeneous Processors. 8th IEEE Heterogeneous Computing Workshop (HCWā99),Apr. 1999, pp. 3ā14
L. Wang, H. J. Siegel and V. P. Roychowdhury. A Genetic-Algorithm-Based Approach for Task Matching and Scheduling in Heterogeneous Computing Environments. 5th IEEE Heterogeneous Computing Workshop (HCWā96), Apr. 1996
L. A. Yan, J. K. Antonio. Estimating the Execution Time Distribution for a Task Graph in a Heterogeneous Computing System. 6th IEEE Heterogeneous Computing Workshop (HCWā97), Apr. 1997, pp. 172ā184
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Ā© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Holenarsipur, P., Yarmolenko, V., Duato, J., Panda, D.K., Sadayappan, P. (2000). Characterization and Enhancement of Static Mapping Heuristics for Heterogeneous Systems. In: Valero, M., Prasanna, V.K., Vajapeyam, S. (eds) High Performance Computing ā HiPC 2000. HiPC 2000. Lecture Notes in Computer Science, vol 1970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44467-X_4
Download citation
DOI: https://doi.org/10.1007/3-540-44467-X_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41429-2
Online ISBN: 978-3-540-44467-1
eBook Packages: Springer Book Archive