Citation:

Giunta, A.A., Swiler, L.P., Brown, S.L., Eldred, M.S., Richards, M.D., and Cyr, E.C., The Surfpack Software Library for Surrogate Modeling of Sparse Irregularly Spaced Multidimensional Data, paper AIAA-2006-7049 in the Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, VA, Sept. 6-8, 2006.

Abstract:

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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Last updated June 22, 2008