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Gpufit: An open-source toolkit for GPU-accelerated curve fitting

Adrian Przybylski, Bjorn Thiel, Jan Keller-Findeisen, Bernd Stock, Mark Bates
Department of NanoBiophotonics, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, Gottingen 37077, Germany
bioRxiv preprint 10.1101/174110, 2017

@article{Przybylski174110,

   author={Przybylski, Adrian and Thiel, Bj{"o}rn and Keller-Findeisen, Jan and Stock, Bernd and Bates, Mark},

   title={Gpufit: An open-source toolkit for GPU-accelerated curve fitting},

   year={2017},

   doi={10.1101/174110},

   publisher={Cold Spring Harbor Labs Journals},

   URL={http://www.biorxiv.org/content/early/2017/08/10/174110},

   eprint={http://www.biorxiv.org/content/early/2017/08/10/174110.full.pdf},

   journal={bioRxiv}

}

We present a general purpose, open-source software library for estimation of non-linear parameters by the Levenberg-Marquardt algorithm. The software, Gpufit, runs on a Graphics Processing Unit (GPU) and executes computations in parallel, resulting in a significant gain in performance. We measured a speed increase of up to 42 times when comparing Gpufit with an identical CPU-based algorithm, with no loss of precision or accuracy. Gpufit is designed such that it is easily incorporated into existing applications or adapted for new ones. Multiple software interfaces, including to C, Python, and Matlab, ensure that Gpufit is accessible from most programming environments. The full source code is published as an open source software repository, making its function transparent to the user and facilitating future improvements and extensions. As a demonstration, we used Gpufit to accelerate an existing scientific image analysis package, yielding significantly improved processing times for super-resolution fluorescence microscopy datasets.
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