Performance Prediction in Production Environments

  • Authors:
  • Affiliations:
  • Venue:
  • IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
  • Year:
  • 1998

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Abstract

Accurate performance predictions are difficult to achieve for parallel applications executing on production distributed systems. Conventional point-valued performance parameters and prediction models are ofen inaccurate since they can only represent one point in a range of possible behaviors. We address this problem by allowing characteristic application and system data to be represented by a set of possible values and their probabilities, which we call stochastic values.In this paper, we give a practical methodology for using stochastic values as parameters to adaptable performance prediction models. We demonstrate their usefulness for a distributed SOR application, showing stochastic values to be more effective than single (point) values in predicting the range of application behavior that can occur during execution in production environments.