A few months ago, I had the innocent intention to wrap LDLt decomposition routines of LAPACK into SciPy but then I am made aware that the minimum required version of LAPACK/BLAS was due to Accelerate framework. Since then I've been following the core SciPy team and others' discussion on this issue.
We have been exchanging opinions for quite a while now within various SciPy issues and PRs about the ever-increasing Accelerate-related issues and I've compiled a brief summary about the ongoing discussions to reduce the clutter. First, I would like to kindly invite everyone to contribute and sharpen the cases presented here https://github.com/scipy/scipy/wiki/Dropping-support-for-Accelerate The reason I specifically wanted to post this also in NumPy mailing list is to probe for the situation from the NumPy-Accelerate perspective. Is there any NumPy specific problem that would indirectly effect SciPy should the support for Accelerate is dropped?
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