- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hello Intel Developer Community,
I'm currently working on a Python project that involves heavy numerical computations, and I want to leverage Intel Math Kernel Library (MKL) for optimized performance. However, I'm facing integration issues in my Python environment.
Specifics of the Issue:
- I have installed Intel one API Base Toolkit, including the MKL component.
- When trying to import MKL or use MKL functions in my Python script, I encounter import errors or runtime issues.
Steps I've Taken:
- Verified that Intel MKL is correctly installed by checking the installation directory.
- Tried reinstalling the one API toolkit and ensuring that the necessary environment variables are set.
- Checked the Python environment for conflicting packages.
My Questions:
- Has anyone successfully integrated Intel MKL into a Python environment?
- Are there specific steps or configurations required for seamless integration?
- Any recommendations for troubleshooting MKL-related issues in a Python project?
I appreciate any guidance or insights from the community. Let's work together to resolve this integration challenge!
Thank you,
Michael Jordy
Link Copied
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi Michael,
Thank you for posting in the Intel® Distribution for Python* community forum. The easiest way to leverage oneMKL in Python is to install the Intel® Distribution for Python*. We recommend installing it via conda. If you don't have conda installed on your system, you can get started with miniconda. The following command will create a new environment and install Intel® Distribution for Python*.
conda create -n idp intelpython3_core
You can also specify the python version:
conda create -n idp intelpython3_core python=3.x
Before confirming the installation, you will see the packages included with the Intel® Distribution for Python*, including MKL ones. After successfully installing it, you can use numpy and scipy as you would normally do and it will automatically take advantage of oneMKL.
Best,
Stef

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page