phase_ret

Tools for optical wavefront reconstruction via non-linear optimization. The code implements the algorithm described by Brady & Fienup [1], which relies on intensity measurements in several defocused planes.

Using CUDA-accelerated transforms on Windows

Installing CUDA, pyCUDA and scikit-cuda on Windows can be a bit troublesome. Here are some tips for a successful setup:

1. After installing the CUDA toolkit, to install pyCUDA and scikit-cuda via pip, make sure that the following directories are present in your PATH environment variable:

   • C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\bin
   • C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin
   • C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\include

   If your install directories differ from defaults, modify the above accordingly.

2. The current stable release of scikit-cuda available via pip is 0.5.1. Unfortunately, it does not support CUDA 8.0. One solution is to build the development release, which has the issue fixed. Another option is to use the 0.5.1 verson with the following simple hack. In your python directory, go to Lib\site-packages\skcuda and replace the line:

    _version_list = [7.5, 7.0, 6.5, 6.0, 5.5, 5.0, 4.0]
   

   with

    _version_list = [8.0, 7.5, 7.0, 6.5, 6.0, 5.5, 5.0, 4.0]
   

   in all of the following files: cublas.py, cudart.py, cufft.py, cusolver.py, cusparse.py. This will ensure that scikit-cuda can locate correct CUDA DLLs.

[1] G. R. Brady and J. R. Fienup. Nonlinear optimization algorithm for retrieving the full complex pupil function. Optics Express, 14(2):474, 2006. doi:10.1364/OPEX.14.000474.