Comment by kxyvr

A similar issue has come up for codes that I write. Among other things, I write low level mathematical optimization codes that need fast linear algebra to run effectively. While there's a lot of emphasis on BLAS/LAPACK, those libraries work on dense linear algebra. In the sparse world, there are fewer good options. For things like sparse QR and Choleski, the two fastest codes that I know about are out of SuiteSparse and Intel MKL. I've not tried it, but the SuiteSparse routines will probably work fine on ARM chips, but they're dual licensed GPL/commercial and the commercial license is incredibly expensive. MKL has faster routines and is completely free, but it won't work on ARM. Note, it works fantastically well on AMD chips. Anyway, it's not that I can't make my codes work on the new Apple chips, but I'd have to explain to my commercial clients that there's another $50-100k upcharge due to the architecture change and licensing costs due to GPL restrictions. That's a lot to stomach.