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GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

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Notes on building the qi2lab fork of Gpufit:

First clone the repository

git clone https://github.com/QI2lab/Gpufit.git
cd Gpufit

building on Windows

The build instructions for the Gpufit source suggest using Visual Studio 2013. However, this version is not compatible with certain all versions of CUDA/nvcc.

For example, with CUDA 11.2 the build files can be created with CMake using

cmake -G "Visual Studio 16 2019" C:\Sources\Gpufit

See my example batch files for Windows. This script will generate Visual Studio project files.

Then, navigate to the build directory and open ALL_BUILD.vcxproj with Visual Studio. Go to build -> build solution and build the project.

building on Linux

The Gpufit source code can be built on Linux using cmake and make. See my example shell script

Installing pygpufit

After compiling, the python package is located in either <build directory>\pyGpufit or <build directory>\Debug\pyGpufit depending on your build options Navigate to this folder, activate your conda or virtual environment, and install with pip install .

Gpufit

Levenberg Marquardt curve fitting in CUDA.

Homepage: github.com/gpufit/Gpufit

The manuscript describing Gpufit is now published in Scientific Reports.

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.

Documentation

Documentation Status

Documentation for the Gpufit library may be found online (latest documentation), 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.

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

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.

  • 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, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

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