An Executable Analytical Performance Evaluation Approach for Early Performance Prediction

  • Authors:

  • Adeline Jacquet;Vincent Janot;Clement Leung;Guang R. Gao;R. Govindarajan;Thomas L. Sterling

  • Affiliations:

  • Institut National des Telecommunications, Evry, France;Institut National des Telecommunications, Evry, France;University of Delaware, Newark, DE;University of Delaware, Newark, DE;Supercomputer Education and Research Centre and Department of Computer Science, India Institute of Science, Bangalore, India;California Institute of Technology, Pasadena, CA

  • Venue:
  • IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
  • Year:
  • 2003

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Abstract

Percolation has recently been proposed as a key component of an advanced program execution model for future generation high-end machines featuring adaptive data/code transformation and movement for effective latency tolerance. An early evaluation of the performance effect of percolation is very important in the design space exploration of future generations of supercomputers. In this paper, we develop an executable analytical performance model of a high performance multi-threaded architecture that supports percolation. A novel feature of our approach is modeling interactions between software (program) and hardware (architecture) components. We solve the analytical model using a queuing simulation tool enriched with synchronization. The proposed approach is effective and facilitates obtaining performance trends quickly. Our results indicate that percolation brings in significant performance gains (by a factor of 2.7 to 11). Further, our results reveal thatpercolation and multithreading can complement each other.