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GPU-accelerated Levenberg-Marquardt curve fitting in CUDA
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# Gpufit
Levenberg Marquardt curve fitting in CUDA.
Homepage: [github.com/gpufit/Gpufit](https://github.com/gpufit/Gpufit)
The manuscript describing Gpufit is now published in [Scientific Reports](https://www.nature.com/articles/s41598-017-15313-9).
## Quick start instructions
To verify that Gpufit is working correctly on the host computer, go to the folder gpufit_performance_test of the binary package and run Gpufit_Cpufit_Performance_Comparison.exe. Further details of the test executable can be found in the documentation package.
## Binary distribution
The latest Gpufit binary release, supporting Windows 32-bit and 64-bit machines, can be found on the [release page](https://github.com/gpufit/Gpufit/releases).
## Documentation
[](http://gpufit.readthedocs.io/en/latest/?badge=latest)
Documentation for the Gpufit library may be found online ([latest documentation](http://gpufit.readthedocs.io/en/latest/?badge=latest)), and also
as a PDF file in the binary distribution of Gpufit.
## Building Gpufit from source code
Instructions for building Gpufit are found in the documentation: [Building from source code](https://github.com/gpufit/Gpufit/blob/master/docs/installation.rst).
## Using the Gpufit binary distribution
Instructions for using the binary distribution may be found in the documentation. The binary package contains:
- The Gpufit SDK, which consists of the 32-bit and 64-bit DLL files, and
the Gpufit header file which contains the function definitions. The Gpufit
SDK is intended to be used when calling Gpufit from an external application
written in e.g. C code.
- Gpufit Performance test: A simple console application comparing the execution speed of curve fitting on the GPU and CPU. This program also serves as a test to ensure the correct functioning of Gpufit.
- Matlab 32 bit and 64 bit bindings, with Matlab examples.
- Python version 2.x and version 3.x bindings (compiled as wheel files) and
Python examples.
- Java binding, with Java examples.
- The Gpufit manual in PDF format
## Examples
There are various examples that demonstrate the capabilities and usage of Gpufit. They can be found at the following locations:
- /examples/c++ - C++ examples for Gpufit
- /examples/c++/gpufit_cpufit - C++ examples that use Gpufit and Cpufit
- /examples/matlab - Matlab examples for Gpufit including spline fit examples (also requires [Gpuspline](https://github.com/gpufit/Gpuspline))
- /examples/python - Python examples for Gpufit including spline fit examples (also requires [Gpuspline](https://github.com/gpufit/Gpuspline))
- /Cpufit/matlab/examples - Matlab examples that only uses Cpufit
- /Gpufit/java/gpufit/src/test/java/com/github/gpufit/examples - Java examples for Gpufit
## Authors
Gpufit was created by Mark Bates, Adrian Przybylski, Björn Thiel, and Jan Keller-Findeisen at the Max Planck Institute for Biophysical Chemistry, in Göttingen, Germany.
## How to cite Gpufit
If you use Gpufit in your research, please cite our publication describing the software. A paper describing the software was published in Scientific Reports. The open-access manuscript is available from the Scientific Reports website, [here](https://www.nature.com/articles/s41598-017-15313-9).
* Gpufit: An open-source toolkit for GPU-accelerated curve fitting
Adrian Przybylski, Björn Thiel, Jan Keller-Findeisen, Bernd Stock, and Mark Bates
Scientific Reports, vol. 7, 15722 (2017); doi: https://doi.org/10.1038/s41598-017-15313-9
## License
MIT License
Copyright (c) 2017 Mark Bates, Adrian Przybylski, Björn Thiel, and Jan Keller-Findeisen
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, anExcerpt of 4,727 characters
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