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Reseach Article

Study of Various Partitioning Policies of Multiprocessor Systems

Published on May 2013 by Harpreet Kaur, Sukhpreet Kaur
National Conference on Structuring Innovation Through Quality SITQ 2013
Foundation of Computer Science USA
SITQ - Number 1
May 2013
Authors: Harpreet Kaur, Sukhpreet Kaur
2fd31be6-43b8-4c05-bb7d-46c934535b76

Harpreet Kaur, Sukhpreet Kaur . Study of Various Partitioning Policies of Multiprocessor Systems. National Conference on Structuring Innovation Through Quality SITQ 2013. SITQ, 1 (May 2013), 36-38.

@article{
author = { Harpreet Kaur, Sukhpreet Kaur },
title = { Study of Various Partitioning Policies of Multiprocessor Systems },
journal = { National Conference on Structuring Innovation Through Quality SITQ 2013 },
issue_date = { May 2013 },
volume = { SITQ },
number = { 1 },
month = { May },
year = { 2013 },
issn = 0975-8887,
pages = { 36-38 },
numpages = 3,
url = { /proceedings/sitq/number1/12058-1314/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Structuring Innovation Through Quality SITQ 2013
%A Harpreet Kaur
%A Sukhpreet Kaur
%T Study of Various Partitioning Policies of Multiprocessor Systems
%J National Conference on Structuring Innovation Through Quality SITQ 2013
%@ 0975-8887
%V SITQ
%N 1
%P 36-38
%D 2013
%I International Journal of Computer Applications
Abstract

Many techniques of partitioning the processing elements have been developed since past few years to improve the performance of the system. A common approach is to divide the set of processing elements into independent partitions depending upon the job requirements. This can be done statically, dynamically or adaptively depending upon current requirements and workload characteristics of the particular job. This paper presents several partitioning policies, which are commonly used to partition the set of processing elements to improve the performance of the multiprocessor systems.

References
  1. Nedal Kafri, Jawad Abu Sbeih "Simple Near Optimal Partitioning Approach to Perfect Triangular Iteration Space. " Proceedings of the 2008 High Performance Computing & Simulation Conference ©ECMS
  2. A. Hariprasad Kodancha, "Time Management in Partitioned Systems" Master's Thesis, Department of Computer Science and Automation Indian Institute of Science Bangalore, October 2007.
  3. Mark S. Squillante, "On the Benefits and Limitations of dynamic Partitioning in Parallel Computer Systems"
  4. E. Rosti, E. Smirni, L. W. Dowdy, G. Serazzi, B. M. Carlson, "Robust Partitioning Policies of Multiprocessor Systems. " Matematical Sciences Section of Oak Ridge National Laboratory. 1993
  5. Stergios V. Anastasiadis and Kenneth C. Sevcik, "A parallel workload model and its implications for processor allocation" High Performance Distributed Computing, 1997, Proceedings. The Sixth IEEE International Symposium on Aug, 1997.
  6. J. H. Abawajy,"An efficient adaptive Scheduling policy for high performance computing" Future Generation Computer systems, Vol. 25, 364-370, (2009).
  7. Srividya Srinivasan, Vijay Subramani, Rajkuman Kettimuthu, Parveen Holenarsipur and P. Sadayappan," Effective Selection of Partition sizes for Moldable Scheduling of Parallel Jobs" Proceeding in – HiPC '02 Proceedings of the 9th International Conference on High Performance Computing Springer-Verlag London, UK ©2002
  8. Allen B. Downey,"A parallel workload model and its implications for processor allocation" Report No. UCB/CSD-96-922, November 1996.
  9. Amit Chhabra, Gurvinder Singh," An Improved Adaptive Space-Sharing Scheduling Policy for Non-dedicated Heterogeneous Cluster Systems "International Journal of Computer Applications and Technology Volume 1- Issue 2, 2012, 57-63.
  10. S. P. Dandamudi and Z. Zhou, "Performance of Adaptive Space-Sharing Policies in Dedicated Heterogeneous Cluster Systems", Future Generation Computer Systems, 20(5), 895-906 (2004).
  11. Young-Chul Shim, "Performance evaluation of scheduling schemes for NOW with heterogeneous computing power", Future Generation Computer Systems. 20(2): 229-236 (2004).
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Partitioning Equipartitioning Multiprocessors Partitioning Policies Scheduling Performance