Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.
@Valentyn I updated my answer as to how to determine which libraries your Python distro. are linked to. I think the Python that ships with your mac is older and relies on the accelerate framework libraries, whereas if you use a Virtual environment software like Anaconda, they ship with different libraries. Your milage may vary, but the Intel MKL libs are probably your best bet if you're using an Intel machine.
You have read correctly, it is indeed important which library numpy is linked against. Depending on your machine and the linked library, you will see varying levels of performance. To verify which libraries are linked to your numpy execute the following in terminal: pythonimport numpy as npnp.__config__.show()
@Valentyn I am not sure what you mean by "turn it on or off". These are libraries, meaning that if you are going to use them in Objective C or Swift code you need to link them. I use these kinds of libraries for computational chemistry calculations, but have to define the /Path/To/Libraries when I want to link them to a binary. What are you trying to accomplish?
The author of the OP is asking about linear algebra libraries that are included with macOS, specifically LAPACK (Linear Algebra PACKage), BLAS (Basic Linear Algebra Subprograms), and ATLAS (Automatically Tuned Linear Algebra Software). These libraries are included in the Accelerate framework, documentation can be found here: developer.apple.com/documentation/accelerate/blas