Hi. I want to implement the code below using vDSP. for i in a.indices { a[i] = n[i] == 0.0 ? 0.0 : b[i] / n[i] } This code is slow. Are there any good implementation using Accelerate framework?

I'm using M1pro and have successfully installed Numpy with Accelerate following, and it really speedup my programs. I also ran np.test() to check the correctness and every test passed. However, I can't install Scipy with Accelerate, since the official document said Accelerate has a LAPACK of too old version. I can't even find a scipy that can pass scipy.test(). I tried the codes below: conda install numpy 'libblas=*=*accelerate' conda install scipy np.test() as fails, sp.test() can't even finish conda install numpy 'libblas=*=*openblas' conda install scipy Both np.test() and sp.test() can finish, but with many failures. I believe the bugs are due to Conda. pip install --no-binary :all: --no-use-pep517 numpy pip install scipy np.test() has no failure and went fast, sp.test() uses OpenBLAS and has 3 failures. This is the best version I have found. So my question is: can we find a reliable version of scipy on M1? Considering the popularity of scipy, I think it's not a high-living expectation. And a question for Apple: is there really a plan to upgrade the LAPACK in Accelerate?