Abstract

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,

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