How to cook with SIMD?

[atravers]

Out of a (web)search for haskell ghc simd poor performance, this:

Optimiser performance problems

I’ve written the infinity norm version of the Adam gradient descent optimiser below. It should work with most multivariate convex problems. It seems to work ok except it is epically slow. Optimising x^2 - x with a bad starting point (e.g. -2000) as shown below in the test1 function takes about 9 seconds. Is there something I can do to make this orders of magnitude faster? I don’t see any straightforward, SIMD options, but I could be wrong? Perhaps a more Haskell friendly way to restate the comp…

seems to be the most recent of the first six “vaguely-relevant” results - does anything there help?