A Survey of the State of the Art in Performance Modeling and Prediction of Parallel and Distributed Computing Systems
Sabri Pllana, Ivona Brandic, Siegfried BenknerAbstract: Performance is one of the key features of parallel and distributed computing systems. Therefore, in the past a significant research effort was invested in the development of approaches for performance modeling and prediction of parallel and distributed computing systems. In this paper we identify the trends, contributions, and drawbacks of the state of the art approaches. We describe a wide range of the performance modeling approaches that spans from the highlevel mathematical modeling to the detailed instruction-level simulation. For each approach we describe how the program and machine are modeled and estimate the model development and evaluation effort, the efficiency, and the accuracy. Furthermore, we present an overall evaluation of the described approaches.
Keywords:
Auto Associative Neural Networks, Modified Great Deluge Algorithm, Soft Computing and Bankruptcy prediction in banks.
doi:10.5019/j.ijcir.2004.121
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