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| Analysis & Integrated Modeling of the Performance Evaluation Techniques for Evaluating Parallel Systems.
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International Journal of Computer Science and Security (IJCSS) |
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Volume: 1 Issue: 1 |
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Pages: 1-96 |
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Publication
Date: June 2007 |
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ISSN
(Online): 1985-1553 |
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1 - 10 |
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Published
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30-06-2007 |
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CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
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| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Integrated model, Metrics, Parallel systems, Performance, Evaluation |
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| Parallel computing has emerged as an environment for computing inherently parallel and
computation intensive applications. Performance is always a key factor in determining
the success of any system. So parallel computing systems are no exception. Evaluating
and analyzing the performance of parallel systems is an important aspect of parallel
computing research. Evaluating and analyzing parallel system is difficult due to the
complex interaction between application characteristics and architectural features.
Experimental measurement, Theoretical/Analytical modeling and Simulation are
the most widely used techniques in the performance evaluation of parallel systems.
Experimental measurement uses real or synthetic workloads, usually known as
benchmarks, to evaluate and analyze their performance on actual hardware.
Theoretical/Analytical models try to abstract details of a parallel system. Simulation and
other performance monitoring/visualization tools are extremely popular because they can
capture the dynamic nature of the interaction between applications and architectures. Each
of them has several types. For example, Experimental measurement has software,
hardware, and hybrid. Theoretical/Analytical modeling has queueing network, Petri net,
etc. and simulation has discrete event, trace/execution driven, Monte Carlo. Each of
these three techniques has their own pros and cons.
The purpose of this paper is firstly to present a qualitative parametric comparative
analysis of these techniques based on parameters like stage, output statistics, accuracy,
cost, resource consumption, time consumption, flexibility, scalability, tools required,
trustability and secondly to justify the need for an integrated model combining the
advantages of all these techniques to evaluate the performance of parallel systems and
thirdly to present a new integrated model for performance evaluation . This paper also
discusses certain issues like selecting an appropriate metric for evaluating parallel
systems. |
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| Amit Chhabra : Colleagues
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| Gurvinder Singh : Colleagues
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