On Tuesday, 12 June 2018 at 11:10:30 UTC, Per Nordlöw wrote:
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?
Looks interesting, though it seems the author has only just
recently tagged the first two releases (3-4 days ago). That
doesn't mean that I don't agree with your suggestions (more
examples/tutorials, separate GPU & autograd/NN library), just
maybe the author has been more focused on basic functionality for
now.