According to Soumith’s benchmark https://github.com/soumith/convnet-benchmarks 10 (which have not been updated recently), it seems that neon’s custom cuda backend is quite fast, nothing new here we already new that. So, my thought was why not utilize that backend to speed up pytorch since neon is open source project and and there is interoperability since the backend is c/c++. So my question is, are there any restrictions or valid reasons not trying to bring that backend speed to pytorch?
Thanks!