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diff --git a/external/clBLAS/src/wrappers/python/README.txt b/external/clBLAS/src/wrappers/python/README.txt deleted file mode 100644 index 10c3cf8c..00000000 --- a/external/clBLAS/src/wrappers/python/README.txt +++ /dev/null @@ -1,59 +0,0 @@ -pyclBLAS setup and installation -(I've been pronouncing it 'pickleBLAS') ------------------------------------------------------------------------- -A python extention wrapper around clBLAS from https://github.com/clMathLibraries/clBLAS - -Dependencies: -1. clBLAS from https://github.com/clMathLibraries/clBLAS ( develop branch ) -2. PyOpenCL from http://mathema.tician.de/software/pyopencl/ ( 2013.2 minimum ) -3. Cython from http://cython.org/, ( 0.18 minimum ) -4. OpenCL runtime, such as AMD's catalyst package ( AMD v2.9 SDK tested ) - -NOTE: This has been tested with 32-bit python on windows & 64-bit on OpenSUSE - -NOTE: Only sgemm has been wrapped as proof-of-concept - -Build steps: ------------------------------------------------------------------------- -1. First, clone the clBLAS repo from github and make sure to build the -'install' step. This is either 'make install' on linux derivatives or -the 'install' project on Visual Studio projects. This should produce a -'package' directory in your build tree that contains ./include, ./libXX & -./bin. - -Note: it is necessary to build 32-bit clBLAS if using 32-bit python, -and 64-bit clBLAS for 64-bit python. - -2. Install pyopencl. If your python distribution contains a version -of pyopencl that is a minimum of 2013.2, then just install with the -distributions package manager like pypm, pip, easy_install. If not, download -pyopencl yourself and follow its directions to build and install. - -3. Install Cython. If your python distribution contains a version -of cython that is a minimum of .18, then just install with the -distributions package manager like pypm, pip, easy_install. If not, -download cython yourself and follow its directions to build and install. - -4. An OpenCL SDK is required to build, which includes OpenCL header files -and linkable libraries. One such SDK is the AMD APP SDK, which can be -downloaded from http://developer.amd.com/tools-and-sdks/heterogeneous-computing/amd-accelerated-parallel-processing-app-sdk/ - -5. Build the pyclBLAS extention. This is accompished by running setup.py, -which acts as a python makefile. An example install command: -'python setup.py --clBlasRoot=F:\code\GitHub\clMathLibraries\bin\clBLAS\develop\vs11x32\package build_ext --inplace' - -'python setup.py --help' prints additional command line parameters that extend -the traditional distutils options. After successfully building the extention -module, a pyclBLAS.pyd file appears. As shown above, it may be necessary to provide -the setup makefile with the paths of the clBLAS 'package' directory and the -OpenCL SDK directory. Setup.py does attempt to find the OpenCL SDK through -the environment variable AMDAPPSDKROOT or OPENCL_ROOT. - -NOTE: On windows, if using a more recent version of visual studio than 2008, -it may be necessary to trick python to using the newer version of your compiler, -by creating an environment variable that it expects to exist as such: -set VS90COMNTOOLS=%VS110COMNTOOLS% - -NOTE: It may be necessary to copy the clBLAS shared library into -the same directory as the extention module so that it can find -clBLAS at runtime |