Do you use any special hardware (like FPGAs) to mitigate the increase in computational cost or do you rely on standard hardware?

I'm very interested in FHE in the context of machine learning models without requiring access to unencrypted data at any stage (be that training or inference). So far, the performance hit wouldn't make this practical, so I was wondering whether maybe hardware solutions exist to deal with that.