Use of predictive performance modeling during large-scale system installation

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We concern ourselves in this paper with one important application of predictive performance modeling - to validate the measured performance during system installation. In general, models can provide performance and scalability expectations of a system for a given workload. The application characteristics of the ASCI workload utilized in this paper is SAGE, a multidimensional, 3D, multi-material hydrodynamics code with adaptive mesh refinement. We review the salient features of an analytical model of this code that can be applied to predict its performance on a large class of large-scale parallel systems. We then utilize the model to validate system performance on ... continued below

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11 p.

Creation Information

Kerbyson, D. J. (Darren J.); Hoisie, A. (Adolfy) & Wasserman, H. J. (Harvey J.) January 1, 2002.

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Description

We concern ourselves in this paper with one important application of predictive performance modeling - to validate the measured performance during system installation. In general, models can provide performance and scalability expectations of a system for a given workload. The application characteristics of the ASCI workload utilized in this paper is SAGE, a multidimensional, 3D, multi-material hydrodynamics code with adaptive mesh refinement. We review the salient features of an analytical model of this code that can be applied to predict its performance on a large class of large-scale parallel systems. We then utilize the model to validate system performance on a Compaq Alpha-server ES45 Supercomputing system being built at Los Alamos, and expected to grow to 30T peak performance in the next few years. We describe the methodology applied during system installation and upgrades to establish a baseline for the achievable 'real' performance of the system. We show that utilization of predictive performance models is also a powerful debugging tool.

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11 p.

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  • Submitted to LACSI 2002, Santa Fe, NM

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  • Report No.: LA-UR-02-4849
  • Grant Number: none
  • Office of Scientific & Technical Information Report Number: 976242
  • Archival Resource Key: ark:/67531/metadc927436

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • January 1, 2002

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

Description Last Updated

  • Dec. 12, 2016, 1:45 p.m.

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Kerbyson, D. J. (Darren J.); Hoisie, A. (Adolfy) & Wasserman, H. J. (Harvey J.). Use of predictive performance modeling during large-scale system installation, article, January 1, 2002; United States. (digital.library.unt.edu/ark:/67531/metadc927436/: accessed November 18, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.