Abstract
In recent years, Multicore computers have been widely included in cluster systems. They adopt shared memory architectures. However, previous researches on parallel loop self-scheduling did not consider the feature of multicore computers. It is more suitable for shared-memory multiprocessors to adopt OpenMP for parallel programming. In this paper, we propose a performance-based approach that partitions loop iterations according to the performance weighting of cluster nodes. Because the iterations assigned to one MPI process will be processed in parallel by OpenMP threads running by the processor cores in the same computational node, the number of loop iterations to be allocated to one computational node at each scheduling step also depends on the number of processor cores in that node. Experimental results show that the proposed approach performs better than previous schemes.
This work is supported in part by National Science Council, Taiwan R.O.C., under grants no. NSC 96-2221-E-029-019-MY3 and NSC 98-2220-E-029-004.
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
HPC Challenge Benchmark, http://icl.cs.utk.edu/hpcc/
Bennett, B.H., Davis, E., Kunau, T., Wren, W.: Beowulf Parallel Processing for Dynamic Load-balancing. In: Proceedings on IEEE Aerospace Conference, vol. 4, pp. 389–395 (2000)
Chronopoulos, A.T., Andonie, R., Benche, M., Grosu, D.: A Class of Loop Self-Scheduling for Heterogeneous Clusters. In: Proceedings of the 2001 IEEE International Conference on Cluster Computing, pp. 282–291 (2001)
Hummel, S.F., Schonberg, E., Flynn, L.E.: Factoring: a method scheme for scheduling parallel loops. Communications of the ACM 35, 90–101 (1992)
Polychronopoulos, C.D., Kuck, D.: Guided Self-Scheduling: a Practical Scheduling Scheme for Parallel Supercomputers. IEEE Trans. on Computers 36(12), 1425–1439 (1987)
Yang, C.-T., Cheng, K.-W., Shih, W.-C.: On Development of an Efficient Parallel Loop Self-Scheduling for Grid Computing Environments. Parallel Computing 33(7-8), 467–487 (2007)
Yang, C.-T., Cheng, K.-W., Li, K.-C.: An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments. The Journal of Supercomputing 34(3), 315–335 (2005)
Yagoubi, B., Slimani, Y.: Load Balancing Strategy in Grid Environment. Journal of Information Technology and Applications 1(4), 285–296 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, CT., Chang, JH., Wu, CC. (2010). Performance-Based Parallel Loop Self-scheduling on Heterogeneous Multicore PC Clusters. In: Zhang, W., Chen, Z., Douglas, C.C., Tong, W. (eds) High Performance Computing and Applications. Lecture Notes in Computer Science, vol 5938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11842-5_71
Download citation
DOI: https://doi.org/10.1007/978-3-642-11842-5_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11841-8
Online ISBN: 978-3-642-11842-5
eBook Packages: Computer ScienceComputer Science (R0)