📅  最后修改于: 2023-12-03 15:09:23.938000             🧑  作者: Mango
Intel-numpy是一个优化的numerical computation库,它是由Intel开发的,专为Intel架构下的计算机打造的。确保您使用的是Intel-numpy,您的计算机的性能将得到显著的提高。在本文中,我们将提供详细的步骤来安装Intel-numpy。
Intel-numpy需要Python 3.6或更高版本才能运行。我们建议您使用anaconda或miniconda来安装Python环境。
在Terminal或Anaconda Prompt中输入以下命令来创建一个新的conda环境:
conda create --name env_name python=3.6
请根据您的需要更改env_name。
通过以下命令激活conda环境:
conda activate env_name
现在,我们可以安装Intel-numpy了:
conda install -c intel intelpython3_full
我们可以通过以下命令测试我们是否成功地安装了Intel-numpy:
import numpy as np
print(np.__config__.show())
如果安装成功,控制台将会打印出以下信息:
blas_mkl_info:
libraries = ['mkl_rt']
library_dirs = ['C:/Anaconda3/envs/env_name/Library\\lib']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
include_dirs = ['C:/Anaconda3/envs/env_name/Library\\include']
blas_opt_info:
libraries = ['mkl_rt']
library_dirs = ['C:/Anaconda3/envs/env_name/Library\\lib']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
include_dirs = ['C:/Anaconda3/envs/env_name/Library\\include']
lapack_mkl_info:
libraries = ['mkl_rt']
library_dirs = ['C:/Anaconda3/envs/env_name/Library\\lib']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
include_dirs = ['C:/Anaconda3/envs/env_name/Library\\include']
lapack_opt_info:
libraries = ['mkl_rt']
library_dirs = ['C:/Anaconda3/envs/env_name/Library\\lib']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
include_dirs = ['C:/Anaconda3/envs/env_name/Library\\include']
mkl_info:
libraries = ['mkl_rt']
library_dirs = ['C:/Anaconda3/envs/env_name/Library\\lib']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
include_dirs = ['C:/Anaconda3/envs/env_name/Library\\include']
intel_openmp:
libraries = ['iomp5']
library_dirs = ['C:/Anaconda3/envs/env_name/Library\\lib']
include_dirs = ['C:/Anaconda3/envs/env_name/Library\\include']
define_macros = [('WITH_OPENMP', None)]
在本文中,我们提供了安装Intel-numpy的详细步骤。希望这篇文章对您有所帮助。