小编big*_*ner的帖子

没有OpenBLAS,为什么numpy/scipy更快?

我做了两个安装:

  1. brew install numpy (和scipy) --with-openblas
  2. 克隆的GIT存储库(用于numpy和scipy)并自己构建它

在克隆了两个方便的脚本以在多线程环境中验证这些库之后:

git clone https://gist.github.com/3842524.git
Run Code Online (Sandbox Code Playgroud)

然后对于我正在执行的每个安装show_config:

python -c "import scipy as np; np.show_config()"
Run Code Online (Sandbox Code Playgroud)

对于安装1来说一切都很好:

lapack_opt_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/opt/openblas/lib']
    language = f77
blas_opt_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/opt/openblas/lib']
    language = f77
openblas_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/opt/openblas/lib']
    language = f77
blas_mkl_info:
    NOT AVAILABLE
Run Code Online (Sandbox Code Playgroud)

但安装2事情并不那么光明:

lapack_opt_info:
    extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
    extra_compile_args = ['-msse3']
    define_macros = [('NO_ATLAS_INFO', 3)]
blas_opt_info:
    extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
    extra_compile_args = ['-msse3', '- …
Run Code Online (Sandbox Code Playgroud)

python performance numpy scipy openblas

4
推荐指数
1
解决办法
3403
查看次数

标签 统计

numpy ×1

openblas ×1

performance ×1

python ×1

scipy ×1