nanaxezy.blogg.se - Numpy and scipy

#Numpy and scipy how to#
#Numpy and scipy install#
#Numpy and scipy update#

PyMKL (0.0.3) - Python wrapper of Intel MKL routines Mkl-static (2018.0.0) - Math library for Intel and compatible processorsĬyanure-mkl-no-openmp (0.21.post3) - optimization toolbox for machine learning Spams-mkl (2.6.1) - Python interface for SPAMS Numpy-mkl (1.10.2) - NumPy: array processing for numbers, strings, records, and Mkl-include (2019.0) - Math library for Intel and compatible processors Mkl-devel (2018.0.3) - Math library for Intel and compatible processorsĬyanure-mkl (0.21.post3) - optimization toolbox for machine learning Mxnet-mkl (1.6.0) - MXNet is an ultra-scalable deep learning framework. Using Intel (R) Math Kernel Library, mirroring numpy.random, butĮxposing all choices of sampling algorithms available in MKL. Mkl-random (1.0.1.1) - NumPy-based implementation of random number generation sampling Mkl (2019.0) - Math library for Intel and compatible processors Sparse-dot-mkl (0.4.1) - Intel MKL wrapper for sparse matrix multiplication Mkl-fft (1.0.6) - MKL-based FFT transforms for NumPy arrays List of available pip packages: $ pip search mkl # intelpython is disabled because not signed (apt upgrade gives error message)

#Numpy and scipy install#

Should I maybe install something else before the above commands ?Ĭontent of /etc/apt//: $ cat /etc/apt//intelproducts.list I didn't need to pip uninstall numpy because mkl environment is brand new and no numpy is in there.

same with intel-scipy and numpy-mkl (same error message).

pip install intel-numpy (error message follows).

then I tried the following pip install commands.

There are many (see list below) and I am in doubt of what to install.

activated the mkl virtual environment ( pyenv activate mkl), and checked the available packages with pip search mkl and pip search intel.

#Numpy and scipy update#

I ran apt update and apt upgrade (succesfully).

I have registered the intel repositories in `apt`, see the file /etc/apt/intelproducts.list in code section below.

#Numpy and scipy how to#

I NEED CLEAR INSTRUCTIONS HOW TO PROCEED (which packages to install) (Python version of that environment is 3.7.6) I want to install intel-numpy or numpy-mkl (clarification needed!) in a pyenv/virtualenv environment with the `pip install` command. I am trying to make my python3/numpy scripts go faster, by using MKL which supposedly will use many or all processor cores/threads. I am on an Asus notebbok with an i7 8550 processor, OS is Ubuntu 18.04.