GPU based Multi-View Deconvolution using cuFFT

This package aims at providing an easy-to-use API for calling GPU deconvolution routines from the Fiji/SPIM_Registration plugin ( https://github.com/fiji/spimreconstruction ). It is written in C++ and offers a C API of plain methods and C structs to call from any client binary or library. The implementation is based on http://arxiv.org/abs/1308.0730.

Building the Library

Operating Systems

We currently support the following operating systems:

• OSX 10.8 or higher (experimental)
• Fedora Linux 19 or higher
• CentOS Linux 6.3 or higher

Dependencies

• CUDA 5 or later (the nvcc compiler, libcudart and libcufft) must be available.
• cmake versions later than 2.8 ( FindCUDA.cmake sources are needed )
• boost 1.42 or later
• fftw 3.1 or later

Install:

To compile the shared library libMultiViewNative.so, invoke

$ mkdir build
$ cd build

If a specific installation destination is to be used

$ cmake -DCMAKE_INSTALL_PREFIX=/path/to/lib ..
$ make
$ make install

or else (will install library in system default library paths, administrator rights required)

$ cmake .. 
$ make
$ make install

Using the Library

Note: The GPU is unstable and not yet production ready. The CPU API can be used!

Fiji related

In order to call the GPU methods from Java, simply create a directory called lib/linux64 under the fiji root directory. Create a symlink to libMultiViewNative.so (compiled for your architecture) here.

License

see LICENSE

Contact

For questions, bug reports, improvement suggestions or else, use the github issue tracker of this repo.

Known Issues

On OS X, CUDA is (at the time of writing) INCOMPATIBLE with the installed llvm based compilers used by default (e.g. /usr/bin/c++). To resolve this, the installation procedure uses an llvm based gcc version for compiling and testing.

Disclaimer

The library at hand is an evolving project. It is designed as the native implementation of http://fiji.sc/Multi-View_Deconvolution (cf. http://arxiv.org/abs/1308.0730). The ultimate goal is to implement the performance sensitive parts of the Multi-View_Deconvolution in this library which can provide significant speed-ups: http://on-demand.gputechconf.com/gtc/2015/video/S5208.html (recording of the talk), https://idisk.mpi-cbg.de/~steinbac/gtc2015 (slides)