Enabling interoperation of high performance, scientific computing applications: Modeling scientific data with the sets & fields (SAF) modeling system

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Abstract

This paper describes the Sets and Fields (SAF) scientific data modeling system; a revolutionary approach to interoperation of high performance, scientific computing applications based upon rigorous, math-oriented data modeling principles. Previous technologies have required all applications to use the same data structures and/or meshes to represent scientific data or lead to an ever expanding set of incrementally different data structures and/or meshes. SAF addresses this problem by providing a small set of mathematical building blocks—sets, relations and fields—out of which a wide variety of scientific data can be characterized. Applications literally model their data by assembling these building blocks. A short historical perspective, a conceptual model and an overview of SAF along with preliminary results from its use in a few ASCI codes are discussed.

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Miller, M. C., Reus, J. F., Matzke, R. P., Arrighi, W. J., Schoof, L. A., Hitt, R. T., & Espen, P. K. (2001). Enabling interoperation of high performance, scientific computing applications: Modeling scientific data with the sets & fields (SAF) modeling system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2074, pp. 158–167). Springer Verlag. https://doi.org/10.1007/3-540-45718-6_18

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