Abstract
A key issue in obtaining high performance from a parallel program represented by a Directed A-cyclic Graph (DAG) is to efficiently mapping it into the target system. The problem is generally addressed in terms of task scheduling, where the tasks are the schedulable units of a program. The task scheduling problems have been shown to be NP-complete in general as well as several restricted cases. In order to be of practical use for large applications, scheduling algorithms must guarantee high performance by minimizing the schedule length and scheduling time. In this paper we propose a new task-scheduling algorithm namely, High Performance task Scheduling (HPS) algorithm for heterogeneous computing system with complexity O (v + e) (p+ log v), which provides optimal results for applications represented by DAGs. The performance of the algorithm is illustrated by comparing the schedule length, speedup, efficiency and the scheduling time with existing algorithms reported in this paper. The comparison study based on both randomly generated graphs and graphs of some real applications shows that HPS algorithm substantially outperforms existing algorithms.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Graham, R.L., Lawler, L.E., Lenstra, J.K., Kan, A.H.: Optimization and Approximation in Deterministic Sequencing and Scheduling: A Survey. Annals of Discrete Mathematics, 287–326 (1979)
Cassavant, T., Kuhl, J.A.: Taxonomy of Scheduling in General Purpose Distributed Memory Systems. IEEE Trans. Software Engineering 14(2), 141–154 (1988)
Hui, C.C., Chanson, S.T.: Allocating Task Interaction Graphs to Processors in Heterogeneous Networks. IEEE Trans. Parallel and Distributed Systems 8(9), 908–926 (1997)
EI-Rewini, H., Lewis, T.G.: Scheduling Parallel Program Tasks onto Arbitrary Target Machines. Journal of parallel and Distributed Computing 9, 138–153 (1990)
Iverson, M., Ozguner, F., Follen, G.: Parallelizing Existing Applications in a Distributed Heterogeneous Environments. In: Proc. Heterogeneous Computing Workshop, pp. 93–100 (1995)
Topcuglou, H., Hariri, S., Wu, M.Y.: Performance Effective and Low-Complexity Task Scheduling for Heterogeneous Computing. IEEE Trans. on Parallel and Distributed Systems 13(3) (February 2002)
Kafil, M., Ahmed, I.: Optimal Task Assignment in Heterogeneous Distributed Computing Systems. IEEE Concurrency 6(3), 42–51 (1998)
Dhodhi, M.K., Ahmad, I., Yatama, A.: An Integrated Technique for Task Matching and Scheduling onto Distributed Heterogeneous Computing Systems. Journal of parallel and distributed computing 62, 1338–1361 (2002)
Dogan, A., Ozguner, F.: LDBS: A Duplication Based Scheduling Algorithm for Heterogeneous Computing Systems. Proc. Int’l. Conf. Parallel Processing (ICPP 2002) (2002)
Basker, S., SaiRanga, P.C.: Scheduling Directed A-cyclic Task Graphs On Heterogeneous Network of Workstations to Minimize Schedule Length. In: Proc. ICPPW (2003)
Bajaj, R., Agrawal, D.P.: Improving Scheduling of Tasks in a Heterogeneous Environments. IEEE Trans. on Parallel and Distributed Systems 15(2) (February 2004)
Kim, S.J., Browne, J.C.: A General Approach to a Mapping of Parallel Computation upon Multiprocessors Architectures. In: Proc. int’l Conf. parallel processing, vol. 2, pp. 1–8 (1988)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ilavarasan, E., Thambidurai, P., Mahilmannan, R. (2005). High Performance Task Scheduling Algorithm for Heterogeneous Computing System. In: Hobbs, M., Goscinski, A.M., Zhou, W. (eds) Distributed and Parallel Computing. ICA3PP 2005. Lecture Notes in Computer Science, vol 3719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564621_22
Download citation
DOI: https://doi.org/10.1007/11564621_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29235-7
Online ISBN: 978-3-540-32071-5
eBook Packages: Computer ScienceComputer Science (R0)