NOTE: This library was only tested with CUDA 4.x and 5.x and may not work with more recent versions. We do not currently have the time to update it for more recent CUDA versions, but would gladly accept pull requests addressing this issue.

====================================================

---

/ | | | | \ /\ | | __| _ ) __/ __/ | | (| || | |) / _ \ | ||| _ \ | ( _
_|_/|// _\ || |/| _|_/ 2012 by Jens Wetzl (jens.wetzl@fau.de) and Oliver Taubmann (oliver.taubmann@fau.de)

This work is licensed under a Creative Commons Attribution 3.0 Unported License. (CC-BY) http://creativecommons.org/licenses/by/3.0/

The CUDA L-BFGS library offers GPU based nonlinear minimization implementing the L-BFGS method in CUDA.

There is no publication available that covers this library exclusively, but you may consider citing the paper it was introduced in:

Wetzl, J., Taubmann, O., Haase, S., Köhler, T., Kraus, M., and Hornegger, J. (2013). GPU-Accelerated Time-of-Flight Super-Resolution for Image-Guided Surgery. In Meinzer, H.-P., Deserno, T. M., Handels, H., and Tolxdorff, T., editors, Bildverarbeitung für die Medizin 2013, Informatik aktuell, pages 21–26. Springer Berlin Heidelberg.

==================================================== BUILDING

To build (and, if desired, install) the library, you will need CMake (http://cmake.org). The default settings should be fine for regular use, but there are lots of options, e.g. you can

• build a reference implementetation on CPU with either float or double precision (requires Eigen),

• build test cases,

• enable error checking, verbose output and timing

• build example projects that demonstrate how the library is used (cf. /projects directory).

==================================================== INCLUDING THE LIBRARY IN YOUR PROJECTS

If you use CMake for your project, including the CudaLBFGS library is jaw-droppingly easy. In your CMakeLists.txt file, add:

find_package(CudaLBFGS REQUIRED) include_directories(${CUDALBDFS_INCLUDE_DIRS})

...

target_link_libraries(YourExecutable ${CUDALBFGS_LIBRARIES})

If you installed the CudaLBFGS library in a non- standard location, you may also have to set either the environment variable CMAKE_PREFIX_PATH or the CMake variable CUDALBFGS_DIR.

==================================================== USAGE

The basic approach can be described as follows:

1. Implement your cost function in a class that inherits from the appropiate base class declared in cost_function.h

2. Create an object of class lbfgs (lbfgs.h) passing an object of your cost function class in the constructor. Adjust settings of lbfgs to your liking.

3. Run minimization providing an initial guess for the solution. Check the return code to know which stopping criterion was fulfilled.