Question

我注意到当我运行像numpy.dot这样的numpy函数时，我的机器的4个内核将忙于完成工作。这意味着，不知何故，numpy自动理解它可以并行化某些计算。但是，我的机器上实际上有8个内核，所以我想告诉numpy使用它们。你知道怎么做吗？

我已按照Limit number of threads in numpy中的说明进行操作，但它们无效。

我报告下面numpy.show_config()的输出：

lapack_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/home/anfri/anaconda2/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/anfri/anaconda2/include']

blas_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/home/anfri/anaconda2/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/anfri/anaconda2/include']

lapack_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/home/anfri/anaconda2/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/anfri/anaconda2/include']

blas_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/home/anfri/anaconda2/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/anfri/anaconda2/include']

如何设置numpy并行度？

0 个答案: