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The Surfpack Software Library for Surrogate Modeling of Sparse Irregularly Spaced Multidimensional Data
Author(s) -
Anthony Giunta,
Laura Swiler,
Shan Brown,
Michael Eldred,
Mark Richards,
Eric C. Cyr
Publication year - 2006
Publication title -
12th aiaa/issmo multidisciplinary analysis and optimization conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2006-7049
Subject(s) - computer science , software , data mining , algorithm , programming language
Surfpack is a general-purpose software library of multidimensional function approximation methods for applications such as data visualization, data mining, sensitivity analysis, uncertainty quantification, and numerical optimization. Surfpack is primarily intended for use on sparse, irregularly-spaced, n-dimensional data sets where classical function approximation methods are not applicable. Surfpack is under development at Sandia National Laboratories, with a public release of Surfpack version 1.0 in August 2006. This paper provides an overview of Surfpack’s function approximation methods along with some of its software design attributes. In addition, this paper provides some simple examples to illustrate the utility of Surfpack for data trend analysis, data visualization, and optimization.

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