The week's pick
Reseach Article
Article:A Critical Performance Study of Memory Mapping on Multi-Core Processors: An Experiment with k-means Algorithm with Large Data Mining Data Sets
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 9 |
| Year of Publication: 2010 |
| Authors: S. N. Tirumala Rao, E. V. Prasad, N. B. Venkateswarlu |
10.5120/211-358
|
S. N. Tirumala Rao, E. V. Prasad, N. B. Venkateswarlu . Article:A Critical Performance Study of Memory Mapping on Multi-Core Processors: An Experiment with k-means Algorithm with Large Data Mining Data Sets. International Journal of Computer Applications. 1, 9 ( February 2010), 1-8. DOI=10.5120/211-358
Abstract
Increased availability of Multi-Core processors is forcing us to re-design algorithms and applications so as to exploit the available computational power from multiple cores. It is not un-common to employ memory mapping of files in applications involving huge I/O bandwidth to improve the response/service times. This paper mainly focuses on performance of memory mapped files on Multi-Core processors. Experiments are carried out with k-means algorithm, a popular Data mining (DM) clustering algorithm, to explore the potential of Multi-Core hardware under OpenMP API and POSIX threads. Observations are made both with static and dynamic threads of OpenMP. Experiments are also conducted with both simulated and real data sets. Experiments indicate that memory mapping of files gives considerable benefit on Multi-Core processors also. In addition, the benefit increased with increased physical memory size. Also, the benefit of memory mapping with the selected algorithm is increasing with number of cores.
References
- “A UNIX interface for shared memory and memory mapped files under mach” , www.72.14.235.104
- ECE 222 System Programming Concepts lecturer notes on system calls, www.parl.clemson.edu
- fread/ifstream, read/mmap performance results www.lastmind.net.
- Gray, A. and Moore, A. (July.-2004), “Data structures for fast statistics”, Tutorial presented at the International Conference on Machine Learning, Banff, Alberta, Canada.
- I. S. Dhillon and D. S. Modha, “A Data Clustering Algorithm on Distributed Memory Multiprocessors In Large-Scale Parallel Data Mining” , Lecture Notes in Artificial Intelligence, vol. 1759, Springer-Verlag, pp 245-260, March 2000.
- Jiawei Han and Micheline Kamber (2006),”Data Mining concepts and Techniques”, 2nd edition Morgan Kaufmann Publishers, San Francisco.
- Manasi N. Joshi, “Parallel K - Means Algorithm on Distributed Memory Multiprocessors”, Project Report, Computer Science Department University of Minnesota, Twin Cities, Spring 2003.
- N.B.Venkateswarlu, M.B.Al-Daoud and S.A Raberts (1995), “Fast k-means Clustering Algorithms”, University of Leads School of Computer Studies Research Report Series Report 95.18.
- OpenMP Architecture , “OpenMP C and C++ Application Program Interface”, http://www.openmp.org/
- Optimized performance analysis of Apache-1.0.5 server, www.isi.edu
- “Parallel Programming In OpenMP” by Rohit Chandra , Ramesh Menon , Leo Dagum , David Kohr , Dror Maydan and Jeff McDonald, Academic press, A Harcourt Science and Technology Company, USA,2001.
- Rabert cattral and Franz Oppacher Carleton University, Department of Computer Science Intelligent systems research unit, Canada,http://archive.ics.uci.edu/ml/datasets/ Poker+Hand
- S .N. Tirumala Rao, E. V. Prasad, N. B. Venkateswarlu and B. G. Reddy, “Significant performance evaluation of memory mapped files with clustering algorithms”, IADIS International conference on applied computing, Portugal pp .455-460, 2008.
- Tuba Islam,“An unsupervised approach for Automatic Language dentification”, Master Thesis, Bogaziqi University, Istambul, Turkey,2003.
- Yen-Yu chen, Dingquing Gasu, Torsten Suel (2002), “I/O Efficient Techniques for computing page rank”, Department of computer and information science, Polytechnique
Index Terms
Keywords