An adaptive skeletal task farm for grids
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
International Journal of Distributed Systems and Technologies
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Performance engineering can be described as a collection of techniques and methodologies whose aim is to provide reliable prediction, measurement and validation of the performance of applications on a variety of computing platforms. This paper reviews techniques for performance estimation and performance engineering developed at the University of Southampton and presents application case studies in task scheduling for engineering meta-applications, and capacity engineering for a financial transaction processing system. These show that it is important to describe performance in terms of a resource model, and that the choice of models may have to trade accuracy for utility in addressing the operational issues. We then present work from the on-going EU funded Grid project GRIA, and show how lessons learned from the earlier work have been applied to support a viable business model for Grid service delivery to a specified quality of service level. The key in this case is to accept the limitations of performance estimation methods, and design business models that take these limitations into account rather than attempting to provide hard guarantees over performance. We conclude by identifying some of the key lessons learned in the course of our work over many years and suggest possible directions for future investigations. Copyright © 2005 John Wiley & Sons, Ltd.