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            "Intended Audience :: Other Audience",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: C++",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Mathematics",
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        "description": "*****************\nPyViennaCL Readme\n*****************\n\n\nPyViennaCL around the web\n=========================\n\n* `Home page <http://viennacl.sourceforge.net/pyviennacl.html>`_\n* `Documentation <http://viennacl.sourceforge.net/pyviennacl/doc/index.html>`_\n* `GitHub <https://github.com/viennacl/pyviennacl-dev>`_ (`Issue tracker <https://github.com/viennacl/pyviennacl-dev/issues>`_)\n\n\nAbout PyViennaCL\n================\n\n*PyViennaCL* aims to make fast, powerful GPGPU and heterogeneous\nscientific computing really transparently easy, especially for users\nalready using NumPy for representing matrices.\n\nPyViennaCL does this by harnessing the `ViennaCL\n<http://viennacl.sourceforge.net/>`_ linear algebra and numerical computation\nlibrary for GPGPU and heterogeneous systems, thereby making available to Python\nprogrammers ViennaCL\u2019s fast *OpenCL* and *CUDA* algorithms. PyViennaCL does\nthis in a way that is idiomatic and compatible with the Python community\u2019s most\npopular scientific packages, *NumPy* and *SciPy*.\n\nPyViennaCL exposes the following functionality:\n\n* sparse (compressed, co-ordinate, ELL, and hybrid) and dense\n  (row-major and column-major) matrices, vectors and scalars on your\n  compute device using OpenCL;\n* standard arithmetic operations and mathematical functions;\n* fast matrix products for sparse and dense matrices, and inner and\n  outer products for vectors;\n* direct solvers for dense triangular systems;\n* iterative solvers for sparse and dense systems, using the BiCGStab,\n  CG, and GMRES algorithms;\n* iterative algorithms for eigenvalue estimation problems.\n\n\nRequirements\n============\n\nPyViennaCL requires the following build dependencies:\n\n* a C++ compiler;\n* *Python* (2.7+) with *setuptools* [see below];\n* *NumPy* (1.7+);\n* *Sphinx* (1.0+) [if you want to build HTML documentation].\n\nIt is also highly recommended to have an available *OpenCL*\nimplementation, since PyViennaCL was designed for this case. If you do\nnot have OpenCL available, then PyViennaCL will still build and\nfunction, but will not perform to full effect.\n\nIf you have a Boost installation on your system, then PyViennaCL can\nalso optionally use that, rather than the Boost subset shipped with\nthe PyViennaCL sources.\n\nsetuptools\n----------\n\nPyViennaCL uses the Python package `setuptools\n<https://bitbucket.org/pypa/setuptools>`_ for installation. Unless you\nare using **Python 3.4**, which comes with the required pieces, you\nmay need to install setuptools. The **best way to do so**, which will\nalso ensure you have the Python package manager *pip* installed, is to\nfollow `the instructions here\n<http://www.pip-installer.org/en/latest/installing.html>`_.\n\nOpenCL\n------\n\nBy default, you will need an OpenCL implementation. PyViennaCL can\nstill build and function without one, but will not perform to full\neffect.\n\nFor information on how to get an OpenCL implementation on Linux, see this\n`howto <http://wiki.tiker.net/OpenCLHowTo>`_.\nSee also the installation section in the\n`ViennaCL Manual <http://viennacl.sourceforge.net/viennacl-manual-current.pdf>`_\non installation hints for Windows.\n\nIf you have an OpenCL installation that you installed and is not\nmanaged by your system's package manager, then it is likely you will\nneed to use the '--cl-lib-dir' configure option.\n\nIf you do not wish to use OpenCL, then follow the *Custom\ninstallation* instructions below, and use the '--no-use-opencl'\nconfigure option.\n\nExtra requirements for building from source on Windows systems\n--------------------------------------------------------------\n\nIn addition to the components required above, Windows builds require\nthe use of the Windows SDK version specific to the version of your\nPython installation. For instance, when you run Python, if you see the\nfollowing::\n\n  Python 2.7.6 (default, Nov 10 2013, 19:24:18) [MSC v.1500 32 bit (Intel)] on win32\n\nthen you are using a release of Python 2.7 and you are building for a\n32-bit installation of that version. You must therefore choose the SDK\nversion and set the build environment accordingly.\n\nIf you are building for a standard distribution (such as described in\nthe example above) of Python 2.6, 2.7, 3.0, 3.1 or 3.2 (either 32- or\n64-bit), you will need the `Microsoft Windows SDK v7.0 for Windows 7\nand .NET Framework 3.5 SP1\n<http://www.microsoft.com/en-us/download/details.aspx?id=18950>`_.\n\nIf you are building for a standard distribution of Python 3.3 or later\n(32- or 64-bit), you will need the `Microsoft Windows SDK v7.1 for\nWindows 7 and .NET Framework 4\n<https://www.microsoft.com/en-us/download/details.aspx?id=8442>`_.\n\nHaving installed the correct SDK version, you will need to open an SDK\ncommand prompt and issue the following commands, according the\narchitecture of your Python installation.\n\nIf you are building for a 32-bit Python installation, use::\n\n  $> set DISTUTILS_USE_SDK=1\n  $> setenv /x86 /release\n\nIf you are building for a 64-bit Python installation, use::\n\n  $> set DISTUTILS_USE_SDK=1\n  $> setenv /x64 /release\n\nAt this point, you will be able to follow the instructions detailed\nbelow under *Installation*. Issue all commands from within the SDK\ncommand window.\n\nYou might also be interested in the `Python Tools for Visual Studio\n<https://pytools.codeplex.com/>`_, though these are not required\neither for building or using PyViennaCL.\n\n\nInstallation\n============\n\nPlease note that the commands below assume that the various programs\ninvoked are available in your system PATH; if they are not, please\nprovide the full path to the executable on invocation.\n\nThis is especially relevant on Windows systems, where Python is not by\ndefault installed into the path. So, in this case, you might have to\nrun something like::\n\n  $> C:\\Python2.7\\python -m pip install pyviennacl\n\ninstead of just::\n\n  $> pip install pyviennacl\n\nQuick installation using pip\n----------------------------\n\nThe following command should usually be enough to install PyViennaCL,\nas long as you have setuptools and pip installed (see above)::\n\n  $> pip install pyviennacl\n\nIf you have a recent installation of Python (2.7 or 3.3+), and a\nrecent installation of pip (1.4+), then this should be painless.\n\nNote that this command assumes you have OpenCL available, and if you\nare on Linux, an OpenCL SDK.\n\nIf this does not succeed, follow the instructions below.\n\nCustom installation\n-------------------\n\nThese instructions assume a UNIX-like platform (such as a Linux\ndistribution or Mac OS X), but will work on a well-configured Windows\nsystem with little modification.\n\nIf you are building from the release package, move on to the next paragraph.\nIf you are building from git, then before doing anything else,\nnavigate to your PyViennaCL folder and get the external submodules with::\n\n  $> git submodule update --init\n\n(On Windows you usually want to use the git bash for this)\n\nIf you are in a hurry, then the following should just work::\n\n  $> python setup.py build\n  $> sudo python setup.py install\n\nOtherwise, read the configuration options, configure, build and\ninstall::\n\n  $> ./configure.py --help\n  $> ./configure.py --some-options\n  $> python setup.py build\n  $> sudo python setup.py install\n\nTo build the HTML documentation using Sphinx, first install PyViennaCL\nas above, and then run::\n\n  $> cd doc\n  $> make html\n\nafter which HTML documentation will be in doc/_build/html. Or you can\njust access the documentation from within the Python interpreter after\ninstallation::\n\n  >>> import pyviennacl\n  >>> help(pyviennacl)\n\n\nAuthors and Contact\n===================\n\nPyViennaCL was developed during the 2013 *Google Summer of Code* by \n`Toby St Clere Smithe <pyviennacl@tsmithe.net>`_.\n\nViennaCL was developed under the aegis of the *Institute for Microelectronics*\nat the *Vienna University of Technology*.\n\nFor any technical questions related to ViennaCL, please use `our\nmailing list <viennacl-support@lists.sourceforge.net>`_.\n\n\nLicence\n=======\n\n(Py)ViennaCL is distributed under the MIT (X11) License. See the file\nLICENSE in the source root directory.",
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