I just discovered
https://github.com/ShigekiKarita/grain
which seems like a very ambitious and active project for making
dynamic neural networks run on the GPU using D in front of mir
and CUDA.
Are there any long-term goals around this project except for the
title?
It would great if someone (author) could write a little
background-knowledge (tutorial) around the subject of dynamic
neural networks that assists all the details in the examples at
https://github.com/ShigekiKarita/grain/tree/master/example
Further, could parts of grain be refactored out into some generic
CUDA-library for use in domains other than dynamic neural
networks?