I try my best to push ML things into WebGPU and I think it has a future, but performance is not there yet. I have little experience with Vulkan except toy projects, but WebGPU and Vulkan seem very similar
I agree. I don't understand there are so many software engineers who are excited about this. I would only be excited if I was a founder in addition to being a software engineer.
This is hilarious, 5 years ago I built a very similar cli tool based on the same idea and with the same name (whosthere but in Polish, ktotu [0]). I wonder if you used AI to generate the project and the idea
Congrats for the execution, it looks more complete and feature rich and Go is a better choice for sure
Performance is not there yet, honestly. I haven’t focus on running things fast, but it’s one of next directs steps I’ll take. The problem with running it in a browser is that we need to find a way to run the PyTorch itself in a browser and to my best knowledge it’s not there yet. I’m looking at it to close the gap, feel welcome to reach out to collaborate if you’re interested!
Good luck to everyone in achieving their goals and exploring new paths!
To me it's deep learning compilers since mid 2025. I am a person who can't learn just from reading books, so 80% of time I learn by doing (contribute to PyTorch) and 20% of time I read books (now: Engineering a Compiler from Keith Cooper and Linda Torczon) and talk to LLMs to fill gaps in my understanding.
My main quest now is to build a bridge [0] between PyTorch and universal GPU computing world - which I believe WebGPU might become. What it requires is to build is 1) a runtime for executing PyTorch ATen operations on WebGPU by running WGSL shaders and 2) a compiler, so you can use full PyTorch power with @torch.compile
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