Lazy table building for high-dimensional look up table generation

Keith F. Prussing; Christopher E. Cordell Jr.

doi:10.1117/12.2662738

13 June 2023 Lazy table building for high-dimensional look up table generation

Keith F. Prussing, Christopher E. Cordell Jr.

Proceedings Volume 12529, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications; 125290B (2023) https://doi.org/10.1117/12.2662738
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

A common constraint in synthetic data generation is the need to evaluate time and resource intensive equations to model physical systems of interest. In fact, many times one needs to evaluate many such models to build up to the real system of interest. In some cases, it is possible to identify a key set of independent variables that govern the equations of interest, and one can build a look up table for interpolation. However, the down side to this strategy is that many computational resources will be spent computing values that may not be used during a simulation. In this paper, we present a new strategy to lazily evaluate complex calculations to build these multi-dimensional look up tables as needed. The technique relies on identifying the fact that some models are able to reuse partial calculations to generate multiple results in a single invocation. This allows generating a base table in the neighborhood of the initial point of interest. After which, the table is grown as the parameter space expands. This reduces the initial computational cost, and the resultant table can be saved for reuse if desired. In a multiprocessing environment, it would also be possible to generate additional table entries in parallel if those points of interest are known in advance. As a specific example, we apply this technique to computing atmospheric corrections for synthetic image generation.

Conference Presentation

Citation Download Citation

Keith F. Prussing and Christopher E. Cordell Jr. "Lazy table building for high-dimensional look up table generation", Proc. SPIE 12529, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications, 125290B (13 June 2023); https://doi.org/10.1117/12.2662738

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