Abstract
Task scheduling on heterogeneous multi-core systems is NP-complete problem. This paper proposes a novel hybrid static scheduling algorithm named Hybrid Successor Concerned Heuristic-Genetic Scheduling (HSCGS) algorithm. The algorithm is a combination of heuristic and genetic scheduling algorithm. In the first phase we propose a heuristic algorithm named Successor Concerned List Heuristic Scheduling (SCLS) to generate a high quality scheduling result. SCLS algorithm takes the impact of current task’s scheduling to its successor into account. The second phase implements an Improved Genetic Algorithm (IGA) for scheduling, to optimize the scheduling results of SCLS iteratively. The comparison experiments are based on both random generated applications and some real world applications. The performance of HSCGS is compared with some famous task scheduling algorithms, such as HEFT and DLS. The results show that HSCGS is the best of them, and the advantages go up with the increase of the heterogeneous factor of inter-core link bandwidth.
This is a preview of subscription content, log in via an institution to check access.
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
Kumar, R., Tullsen, D., Jouppi, N., Ranganathan, P.: Heterogeneous Chip Multiprocessors. IEEE Computer, 32–38 (November 2005)
Topcuoglu, H., Hariri, S., Wu, M.Y.: Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing. IEEE Trans. Parallel and Distributed Systems 13(3), 260–274 (2002)
Daoud, M.I., Kharma, N.: A hybrid heuristic–genetic algorithm for task scheduling in heterogeneous processor networks. J. Parallel Distrib. Comput. 71, 1518–1531 (2011)
Daoud, M.I., Kharma, N.: A high performance algorithm for static task scheduling in heterogeneous distributed computing systems. J. Parallel Distrib. Comput. 68, 399–409 (2008)
Wen, Y., Xu, H., Yang, J.: A heuristic-based hybrid genetic-variable neighborhood search algorithm for task scheduling in heterogeneous multiprocessor system. Information Sciences 181, 567–581 (2011)
Eswari, R., Nickolas, S.: Path-based Heuristic Task Scheduling Algorithm for Heterogeneous Distributed Computing Systems. In: 2010 International Conference on Advances in Recent Technologies in Communication and Computing (2010)
Kwok, Y.K., Ahmad, I.: Static scheduling algorithms for allocating directed task graphs to multiprocessors. ACM Comput. Surveys 31(4), 406–471 (1999)
Sih, G.C., Lee, E.A.: A compile-time scheduling heuristic for interconnection constrained heterogeneous processor architectures. IEEE Trans. Parallel Distributed Systems 4(2), 175–187 (1993)
Kwok, Y.K., Ahmad, I.: Dynamic critical-path scheduling: an effective technique for allocating task graphs to multiprocessors. IEEE Trans. Parallel Distributed Systems 7(5), 506–521 (1996)
El-Rewini, H., Lewis, T.G.: Scheduling parallel program tasks onto arbitrary target machines. J. Parallel Distributed Comput. 9(2), 138–153 (1990)
Eiben, A.E., Michalewicz, Z., Schoenauer, M., Smith, J.E.: Parameter control in evolutionary algorithms. Stud. Comput. Intell. 54, 19–46 (2007)
Ilavarasan, E., Thambidurai, P., Mahilmannan, R.: Performance effective task scheduling algorithm for heterogeneous computing system. In: Proc. 4th International Symposium on Parallel and Distributed Computing, France, pp. 28–38 (2005)
Iverson, M., Ozguner, F., Follen, G.: Parallelizing existing applications in a distributed heterogeneous environment. In: Proc. 4th Heterogeneous Computing Workshop, Santa Barbara, CA, pp. 93–100 (1995)
Augonnet, C., Thibault, S., Namyst, R., Wacrenier, P.-A.: STARPU: a unified platform for task scheduling on heterogeneous multicore architectures. University of Bordeaux – LaBRI – INRIA Bordeaux Sud-Oues
Moghaddam, M.E., Bonyadi, M.R.: An Immune-based Genetic Algorithm with Reduced Search Space Coding for Multiprocessor Task Scheduling Problem. Int. J. Parallel Prog., doi:10.1007/s10766-011-0179-0
Bansal, S., Kumar, P., Singh, K.: An improved duplication strategy for scheduling precedence constrained graphs inmultiprocessor systems. IEEE Trans. Parallel Distrib. Syst. 14, 533–544 (2003)
Chung, Y.C., Ranka, S.: Application and performance analysis of a compile-time optimization approach for list scheduling algorithms on distributed-memory multiprocessors. In: Proc. Supercomputing 1992, Minneapolis, MN, pp. 512–521 (1992)
Wu, M., Dajski, D.: Hypertool: A programming aid for message passing systems. IEEE Trans. Parallel Distrib. Syst. 1, 330–343 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, C., Gu, J., Wang, Y., Zhao, T. (2012). A Hybrid Heuristic-Genetic Algorithm for Task Scheduling in Heterogeneous Multi-core System. In: Xiang, Y., Stojmenovic, I., Apduhan, B.O., Wang, G., Nakano, K., Zomaya, A. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2012. Lecture Notes in Computer Science, vol 7439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33078-0_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-33078-0_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33077-3
Online ISBN: 978-3-642-33078-0
eBook Packages: Computer ScienceComputer Science (R0)