DocumentCode
451209
Title
Predictive Performance and Scalability Modeling of a Large-Scale Application
Author
Kerbyson, D.J. ; Alme, H.J. ; Hoisie, A. ; Petrini, F. ; Wasserman, H.J. ; Gittings, M.
Author_Institution
Los Alamos National Laboratory
fYear
2001
fDate
10-16 Nov. 2001
Firstpage
39
Lastpage
39
Abstract
In this work we present a predictive analytical model that encompasses the performance and scaling characteristics of an important ASCI application. SAGE (SAIC’s Adaptive Grid Eulerian hydrocode) is a multidimensional hydrodynamics code with adaptive mesh refinement. The model is validated against measurements on several systems including ASCI Blue Mountain, ASCI White, and a Compaq Alphaserver ES45 system showing high accuracy. It is parametric - basic machine performance numbers (latency, MFLOPS rate, bandwidth) and application characteristics (problem size, decomposition method, etc.) serve as input. The model is applied to add insight into the performance of current systems, to reveal bottlenecks, and to illustrate where tuning efforts can be effective. We also use the model to predict performance on future systems.
Keywords
Performance analysis; Teraflop scale computing; full application codes; parallel system architecture; Adaptive mesh refinement; Computer architecture; Government; Hydrodynamics; Laboratories; Large-scale systems; Multidimensional systems; Performance analysis; Predictive models; Scalability; Performance analysis; Teraflop scale computing; full application codes; parallel system architecture;
fLanguage
English
Publisher
ieee
Conference_Titel
Supercomputing, ACM/IEEE 2001 Conference
Print_ISBN
1-58113-293-X
Type
conf
DOI
10.1109/SC.2001.10011
Filename
1592815
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