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[ascl:1505.016] CUTE: Correlation Utilities and Two-point Estimation

CUTE (Correlation Utilities and Two-point Estimation) extracts any two-point statistic from enormous datasets with hundreds of millions of objects, such as large galaxy surveys. The computational time grows with the square of the number of objects to be correlated; technology provides multiple means to massively parallelize this problem and CUTE is specifically designed for these kind of calculations. Two implementations are provided: one for execution on shared-memory machines using OpenMP and one that runs on graphical processing units (GPUs) using CUDA.

Code site:
https://github.com/damonge/CUTE
Used in:
https://ui.adsabs.harvard.edu/abs/2015MNRAS.449..670A https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.1856A
Described in:
https://ui.adsabs.harvard.edu/abs/2012arXiv1210.1833A
Bibcode:
2015ascl.soft05016A

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ascl:1505.016
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