无法使用“英特尔MKL”安装Scipy

我用英特尔MKL成功地从源代码安装了Numpy“Numpy-1.12.0.dev0+1380fdd-py2.7-linux-x86_64.egg”(主要遵循 https://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl ). numpy.show_config() 显示以下内容:

Python 2.7.10 (default, Sep  8 2015, 17:20:17) 
[GCC 5.1.1 20150618 (Red Hat 5.1.1-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
>>> numpy.show_config()
lapack_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/lib/intel64']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/include']
blas_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/lib/intel64']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/include']
lapack_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/lib/intel64']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/include']
blas_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/lib/intel64']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/include']
mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/lib/intel64']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/intel/compilers_and_libraries_2016.1.150/linux/mkl/include']

而且 numpy.test() 工作正常:

>>> numpy.test()
Running unit tests for numpy
NumPy version 1.12.0.dev0+1380fdd
NumPy relaxed strides checking option: True
NumPy is installed in /usr/lib64/python2.7/site-packages/numpy-1.12.0.dev0+1380fdd-py2.7-linux-x86_64.egg/numpy
Python version 2.7.10 (default, Sep  8 2015, 17:20:17) [GCC 5.1.1 20150618 (Red Hat 5.1.1-4)]
nose version 1.3.7
[....................SKIP..........................]
----------------------------------------------------------------------
Ran 5855 tests in 51.180s

OK (KNOWNFAIL=6, SKIP=8)
<nose.result.TextTestResult run=5855 errors=0 failures=0>

但由于某些原因,我甚至无法通过 python setup.py config --compiler=intelem --fcompiler=intelem build_clib --compiler=intelem --fcompiler=intelem build_ext --compiler=intelem --fcompiler=intelem install 也不通过 pip install scipy 。从源收到以下错误:

RuntimeError: Running cythonize failed!

检查cython:

cython -V
Cython version 0.23

通过pip引线将其安装到:

Command "/usr/bin/python -u -c "import setuptools, tokenize;__file__='/tmp/pip-build-ticToS/scipy/setup.py';exec(compile(getattr(tokenize, 'open', open)(__file__).read().replace('\r\n', '\n'), __file__, 'exec'))" install --record /tmp/pip-qnZ8HE-record/install-record.txt --single-version-externally-managed --compile" failed with error code 1 in /tmp/pip-build-ticToS/scipy/

你知道我做错了什么吗?

我的操作系统是Thinkpad T450上的Fedora 23。一个附带问题是,我也认识到 numpy.test() 如果不使用“英特尔MKL”,速度会快得多。对此有什么解释吗?

非常感谢你。