Eiger: A Framework for the Automated Synthesis of Statistical Performance Models

Eiger: A Framework for the Automated Synthesis of Statistical Performance Models

Andrew Kerr, Eric Anger, Gilber Hendry, and Sudhakar Yalamanchili. “Eiger: A framework for the automated synthesis of statistical performance models.” 1st Workshop on Performance Engineering and Applications (WPEA), held with HiPC. December 2012.

Abstract

As processor architectures continue to evolve to increasingly heterogeneous and asymmetric designs, the construction of accurate performance models of execution time and energy consumption has become increasingly more challenging. Models that are constructed, are quickly invalidated by new features in the next generation of processors while many interactions between application and architecture parameters are often simply not obvious or even apparent. Consequently, we foresee a need for an automated methodology for the systematic construction of performance models of heterogeneous processors. The methodology should be founded on rigorous mathematical techniques yet leave room for the exploration and adaptation of a space of analytic models. Our current effort toward creating such an extensible, targeted methodology is Eiger. This paper describes the methodology implemented in Eiger, the specifics of Eiger’s extensible implementation and the results of one scenario in which Eiger has been applied – the synthesis of performance models for use in the simulation-based design space exploration of Exascale architectures.

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Eiger: a Framework for the Automated Synthesis of Statistical Performance Models [Slides]

Citation

@inproceedings{kerr2012,
author = {Kerr, Andrew and Anger, Eric and Hendry, Gilbert and Yalamanchili, Sudhakar},
title = {Eiger: A Framework for the Automated Synthesis of Statistical Performance Models},
booktitle = {Proceedings of the 1st Workshop on Performance Engineering and Applications},
year = {2012},
numpages = {6},
}