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Assessing the role of mini-applications in predicting key performance characteristics of scientific and engineering applications

Journal of Parallel and Distributed Computing

Barrett, R.F.; Crozier, Paul C.; Doerfler, Douglas W.; Heroux, Michael A.; Lin, Paul L.; Thornquist, Heidi K.; Trucano, Timothy G.; Vaughan, Courtenay T.

Computational science and engineering application programs are typically large, complex, and dynamic, and are often constrained by distribution limitations. As a means of making tractable rapid explorations of scientific and engineering application programs in the context of new, emerging, and future computing architectures, a suite of "miniapps" has been created to serve as proxies for full scale applications. Each miniapp is designed to represent a key performance characteristic that does or is expected to significantly impact the runtime performance of an application program. In this paper we introduce a methodology for assessing the ability of these miniapps to effectively represent these performance issues. We applied this methodology to three miniapps, examining the linkage between them and an application they are intended to represent. Herein we evaluate the fidelity of that linkage. This work represents the initial steps required to begin to answer the question, "Under what conditions does a miniapp represent a key performance characteristic in a full app?"

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TYPE Journal Article YEAR 2015
ScopusOSTIDOI

Assessing the predictive capabilities of mini-applications

Proceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012

Barrett, Richard F.; Crozier, Paul C.; Doerfler, Douglas W.; Hammond, Simon D.; Heroux, Michael A.; Lin, Paul L.; Trucano, Timothy G.; Vaughan, Courtenay T.; Williams, Alan B.

The push to exascale computing is informed by the assumption that the architecture, regardless of the specific design, will be fundamentally different from petascale computers. The Mantevo project has been established to produce a set of proxies, or 'miniapps,' which enable rapid exploration of key performance issues that impact a broad set of scientific applications programs of interest to ASC and the broader HPC community. Understanding the conditions under which a miniapp can be confidently used as predictive of an applications' behavior must be clearly elucidated. Toward this end, we have developed a methodology for assessing the predictive capabilities of application proxies. Adhering to the spirit of experimental validation, our approach provides a framework for examining data from the application with that provided by their proxies. In this poster we present this methodology, and apply it to three miniapps developed by the Mantevo project. © 2012 IEEE.

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TYPE Conference YEAR 2012
OSTIScopus
Results 1–25 of 75
Results 1–25 of 75