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Journal Article

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

MPS-Authors
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Przybylski,  A.
Department of NanoBiophotonics, MPI for Biophysical Chemistry, Max Planck Society;

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Thiel,  B.
Department of NanoBiophotonics, MPI for Biophysical Chemistry, Max Planck Society;

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Keller-Findeisen,  J.
Department of NanoBiophotonics, MPI for Biophysical Chemistry, Max Planck Society;

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Bates,  M.
Department of NanoBiophotonics, MPI for Biophysical Chemistry, Max Planck Society;

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Fulltext (public)

2503422.pdf
(Publisher version), 3MB

Supplementary Material (public)

2503422_Suppl.doc
(Supplementary material), 3MB

Citation

Przybylski, A., Thiel, B., Keller-Findeisen, J., Stock, B., & Bates, M. (2017). Gpufit: An open-source toolkit for GPU-accelerated curve fitting. Scientific Reports, 7: 15722. doi:10.1038/s41598-017-15313-9.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002E-3473-4
Abstract
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.