Gregory's Server@philpax @BartWronski @gregmorenz So many of the pieces are in place, and I think it will happen, first by running on WebGPU, then optimizing from there. As @philpax says, wonnx looks pretty good, but being restricted to WGSL leaves a *lot* of performance on the table compared with what GPUs can do.
|
3 comments
 @philpax @BartWronski @gregmorenz I agree. And more to the point, once you actually get it running, then the open source community can incrementally optimizes pieces of it until it runs pretty well. The missing piece (that seems to have very little community interest) is ahead of time compiled shaders, which would also let you do custom WGSL extensions. @raph @philpax @BartWronski @gregmorenz My experience is that this work needs commercial sponsorship of a particular shape. Research framework users generally will only use something free + open source, yet adequate support for a given piece of hardware is way beyond student or hobbyist work. I started a company that built a performance-portable deep learning framework and learned this and many lessons slowly π |
@raph @BartWronski @gregmorenz Yeah, there's definitely a lowest common denominator problem with wgpu, but I imagine it'll be "good enough" for the short to medium term.
In the future, I hope that an actual standard for this kind of ML acceleration is formulated, but it's not really in Team Green's best interests to facilitate that...