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Experimental Evaluation of the Performance of Processing Stealing Technique: A Scalable Load Balancing Technique for a Dynamic Multiprocessor System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 83 - Number 3 |
| Year of Publication: 2013 |
| Authors: O. O. Olakanmi, O. A. Fakolujo |
10.5120/14426-2568
|
O. O. Olakanmi, O. A. Fakolujo . Experimental Evaluation of the Performance of Processing Stealing Technique: A Scalable Load Balancing Technique for a Dynamic Multiprocessor System. International Journal of Computer Applications. 83, 3 ( December 2013), 7-13. DOI=10.5120/14426-2568
Abstract
This paper reports preliminary experimental evaluation of a Processing Elements Stealing (PE-S) technique which was targeted as efficient and scalable load balancing technique for dynamically structured multiprocessor systems. The multiprocessor system is imagined as a dynamic cluster based multiprocessor. Each cluster of the multiprocessor system is a node in symmetric multiprocessor architecture and the number of Processing Element (PE) in each cluster is dynamically determined at runtime. The PE-S technique dynamically computes the configuration ratio using the number of threads in the dynamically assigned tasks to generate the new number of PE for each cluster. This new configuration ratio is thereafter used to balance the additional computational work generated by runtime instantiation of current workloads for each cluster. In this work, the efficiency of the PE-S was evaluated using memory traces of some tightly parallel applications where the amount of parallelism is parameterized. These traces were used as workloads on two different simulation setups; the first is a dynamic multiprocessor with PE-S while the other was also a dynamic multiprocessor but without PE-S. This is to evaluate the performance of the PE-S load balancing technique on the targeted multiprocessor. Also the efficiency of PE-S reconfigurations was compared with other possible reconfiguration ratios. The experimental results showed that the load balancing algorithm is efficient and scalable for balancing at least 100,000 instructions tasks and PE-S generated ratios are averagely better than any other reconfiguration ratios.
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