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A parallel code or CPLS 1.0, based upon the recently invented prediction-augmented Classical Least Squares/Partial Least Squares (PA-CLS/PLS) hybrid algorithm, was developed in order to perform quantitative analyses of spectral data. A parallel routine was desired for fast calculation of full calibration models, cross-validation verification, and true prediction results from large data collections, which are expected to result from two-dimensional infrared (IR) imaging spectroscopy. This report contains a summary of the parallel PA-CLS/PLS hybrid algorithm, the mathematical formulation, and software libraries used in the implementation of the parallel algorithm. An explanation of how to use the three routines in the CPLS 1.0 code--full calibration, cross-validation, and true prediction--is provided along with variable definitions, input file requirements, and output file data formats. In order to demonstrate parallel speed-up, @e added advantage of multiple processors, and communication versus computation times, timing results for each of the three routines are reported for a representative (but small) sample set.

A Parallel Prediction-Augmented Classical Least Squares/Partial Least Squares Hybrid Algorithm: CPLS 1.0 Code