Hi folks:

I've been experimenting with the pymc statespace. One of the downsides I read about is the incompatibility of statespace, at present, with faster samplers. Having said that, JAX could be fast if only I had the right setup, I've read.

I'm using an AMD GPU and a AMD 8 core CPU (16 hyperthreaded), but I'm also using a windows machine. Is there a sure way to speed up JAX, other than having a simple, well specified model?

For example, I've seen where using a special docker image running Linux with a special AMD gpu config could help. I can't afford to get an Nvidia card right now.

I'll point out that this is my current script config:

jax.config.update("jax_platform_name", "cpu")
import numpyro
numpyro.set_host_device_count(8)

Thank you so much for your time!

-Mike