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. 2017 Nov 16;7:15722. doi: 10.1038/s41598-017-15313-9

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Processing speed comparison between three fitting libraries: Gpufit, MINPACK, and GPU-LMFit. (a) Execution speed vs. number of fits per function call (N). (b) Execution speed vs. number of data points per fit, where the size of the simulated 2D Gaussian peaks was varied from 5 × 5 up to 25 × 25 points. For smaller tasks (smaller numbers of fits per call or smaller data sizes) the Gpufit library makes more efficient use of GPU processing resources, outperforming GPU-LMFit by more than one order of magnitude. For larger tasks the results become more similar between the two GPU-based libraries. For details of the simulated data and fit parameters, see the Supplementary Information.