GPU图像加速实现迭代算法加速

----------------------------------------------------------------------- This file is part of the All Scale Tomographic Reconstruction Antwerp Toolbox ("ASTRA Toolbox") Copyright: iMinds-Vision Lab, University of Antwerp License: Open Source under GPLv3 Contact: astra@ua.ac.be Website: http://astra.ua.ac.be http://code.google.com/p/astra-toolbox/ ----------------------------------------------------------------------- The ASTRA Toolbox is a MATLAB toolbox of high-performance GPU primitives for 2D and 3D tomography. We support 2D parallel and fan beam geometries, and 3D parallel and cone beam. All of them have highly flexible source/detector positioning. A large number of 2D and 3D algorithms are available, including FBP, SIRT, SART, CGLS. The basic forward and backward projection operations are GPU-accelerated, and directly callable from MATLAB to enable building new algorithms. Documentation / samples: ------------------------- See the matlab code samples in samples/ and on http://code.google.com/p/astra-toolbox/ . Installation instructions: --------------------------- Windows, binary: ----------------- Add the mex and tools subdirectories to your matlab path. Linux, from source: -------------------- Requirements: g++, boost, CUDA (driver+toolkit), matlab cd build/linux ./configure --with-cuda=/usr/local/cuda \ --with-matlab=/usr/local/MATLAB/R2012a \ --prefix=/usr/local/astra make make install Add /usr/local/astra/lib to your LD_LIBRARY_PATH. Add /usr/local/astra/matlab and its subdirectories (tools, mex) to your matlab path. NB: Each matlab version only supports a specific range of g++ versions. Despite this, if you have a newer g++ and if you get errors related to missing GLIBCXX_3.4.xx symbols, it is often possible to work around this requirement by deleting the version of libstdc++ supplied by matlab in MATLAB_PATH/bin/glnx86 or MATLAB_PATH/bin/glnxa64 (at your own risk). Windows, from source using Visual Studio 2008: ----------------------------------------------- Requirements: Visual Studio 2008, boost, CUDA (driver+toolkit), matlab. Note that a .zip with all required (and precompiled) boost files is available from our website. Set the environment variable MATLAB_ROOT to your matlab install location. Open astra_vc08.sln in Visual Studio. Select the appropriate solution configuration. (typically Release_CUDA|win32 or Release_CUDA|x64) Build the solution. Install by copying AstraCuda32.dll or AstraCuda64.dll from bin/ and all .mexw32 or .mexw64 files from bin/Release_CUDA or bin/Debug_CUDA and the entire matlab/tools directory to a directory to be added to your matlab path. References: ------------ If you use parallel beam GPU code for your research, we would appreciate it if you would refer to the following paper: W. J. Palenstijn, K J. Batenburg, and J. Sijbers, "Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)", Journal of Structural Biology, vol. 176, issue 2, pp. 250-253, 2011