Micro time cost analysis of parallel computations

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Abstract
The authors investigate the modeling and analysis of time cost behavior of parallel computations. It is assumed parallel computations reside in a computer system in which there is a limited number of processors, all the processors have the same speed, and they communicate with each other through a shared memory. It has been found that the time costs of parallel computations depend on the input, the algorithm, the data structure, the processor speed, the number of processors, the processing power allocation, the communication, the execution overhead, and the execution environment. The authors define time costs of parallel computations as a function of the first seven factors as listed. The computation structure model is modified to describe the impact of these seven factors on time cost. Techniques based on the modified computation structure model are developed to analyze time cost. A software tool, TCAS (time cost analysis system), that uses both the analytic and the simulation approaches is designed and implemented to aid users in determining the time cost behavior of their parallel computations.

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