- From: Corentin Wallez <cwallez@google.com>
- Date: Fri, 15 May 2020 17:36:53 +0200
- To: Tianqi Chen <tqchen@cs.washington.edu>
- Cc: public-gpu <public-gpu@w3.org>
- Message-ID: <CAGdfWNMNiA61t+-mTr3KMtbnKpx6XpXFzjsAUGwrLta9rdMcDw@mail.gmail.com>
Hey Tianqi, Thanks for sharing! The blog post was very interesting and the results encouraging. I'm surprised it's this close even when WebGPU doesn't support float16 or subgroup operations yet. Impressive! The samples list in Implementation-Status is very out of date, there's been a lot of people starting to use WebGPU lately. Group, what do you think of having a "WebGPU users" wiki page to collect things beyond the most trivial samples? Apache TVM would fit in there. Cheers, Corentin On Thu, May 14, 2020 at 11:46 PM Tianqi Chen <tqchen@cs.washington.edu> wrote: > Hi WebGPU community: > > I am sending this along since I think it could be interesting to the > members who are also interested in machine learning. > > We recently introduced support for WASM and WebGPU to the Apache TVM deep > learning compiler. > Our pre-liminary experiments shows that TVM’s WebGPU backend can* get > close to native GPU performance* when deploying > deep learning models to the web. Please see the blog here. > > > https://tvm.apache.org/2020/05/14/compiling-machine-learning-to-webassembly-and-webgpu > > I am also wondering if it is possible to link to the blog as an example of > ML On WebGPU in the wiki page( > https://github.com/gpuweb/gpuweb/wiki/Implementation-Status). > As an open source community, we certainly love feedbacks and > collaborations > > Cheers > TQ > >
Received on Friday, 15 May 2020 15:37:27 UTC