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WebGPU. It’ll be live in Chromium stable this Thursday and will be the biggest step change for browser-based GPU since the original WebGL.

• softfalcon 3y ago
  Excited to see WebGPU support for this become stable with three.js! They've been working on it in a beta-state, but I foresee huge perf improvements once it's widely accepted on the major browsers.
  • echelon 3y ago
    Do you see folks continuing to build on top of three.js? It looks like Rust game engines like Bevy and Fyrox are set to deliver comprehensive functionality to the browser over WASM/WebGPU.
    • softfalcon 3y ago
      That’s cool there are WASM enabled Rust engines! I’ll be honest, before you mentioned them, I’d never even heard of Bevy or Fyrox before. As for people continuing to use three.js, yeah, I still see a lot of folks using it to build games. That whole “js everywhere” still seems to be really popular with a lot of folks. It probably also helps that new comp sci students learning 3D graphics are often now taught using three.js instead of C++ like when I was a student.
• dchest 3y ago
  WebGPU is all the rage right now for hosting AI models in browser :)
  • digitallyfree 3y ago
    This project is doing LLMs of all things with WebGPU too! https://mlc.ai/web-llm/ https://mlc.ai/web-llm/
• MuffinFlavored 3y ago
  Are WebGPU "libraries" at a point where instead of being recommended Python + PyTorch for neural network training (then exporting the model to ONNX and turning around and loading it and using it)? If not, how far? I've had trouble understanding why the PyTorch "GPU" (CUDA, MPS, etc.) code can't convert to WASM + WebGPU. Something has to be missing/it has to be a huge effort, but in theory you're supposed to be able to do GPU calculation with WebGPU, right? Seems like the ecosystem is very early/non-existent.
  • bufo 3y ago
    It can be converted, and can be fairly fast, see Tensorflow.js or https://jott.live/markdown/m1_webgpu_perf https://jott.live/markdown/m1_webgpu_perf. However the any “web” standard will always be a subset of what the hardware can truly provide because it has to support ALL GPU vendors. For example leveraging Nvidia Tensor Cores or Apple’s neural accelerator is not possible. For ML training and inference this means that any webGPU implementation is at least ~3x slower (likely much more) vs an optimized CUDA implementation.
    • MuffinFlavored 3y ago
      > Web Shading Language (WSL) The WSL in the article was throwing me off.
    • vhcr 3y ago
      That's not necessarily true, WebGL for example supports extensions.
      • bufo 3y ago
        Correct, but I don’t see Firefox or Chrome bothering to add tensor core support.
  • paulgb 3y ago
    Yes, it's definitely lagging the CUDA ecosystem. I did a write-up a few weeks back on the various approaches people are taking to do inference in the browser (WASM, WebGL, WebGPU): https://digest.browsertech.com/archive/browsertech-digest-the-race-to-run-inference-in/ https://digest.browsertech.com/archive/browsertech-digest-th... Matt Rickard also had a short write-up recently: https://matt-rickard.com/implementing-llms-in-the-browser https://matt-rickard.com/implementing-llms-in-the-browser My take is that we probably won't see much training done on WebGPU, because training is done upfront and it makes sense to standardize on a single GPU vendor and use an interface that can squeeze all the juice out of those GPUs (CUDA). But for inference and run-time computations, it could be very interesting to take a model trained with CUDA/PyTorch and export it (maybe with Apache TVM or tensorflow.js) into WebGPU that can run on end-user devices.
• manojlds 3y ago
  It's directly linked to buzz around ChatGPT
• rumdz 3y ago
  Why is WebGPU a thing rather than just exposing Vulkan in the browser?
  • bckr 3y ago
    This post goes into a lot of detail: https://cohost.org/mcc/post/1406157-i-want-to-talk-about-webgpu https://cohost.org/mcc/post/1406157-i-want-to-talk-about-web...