gpuweb
burn
| gpuweb | burn | |
|---|---|---|
| 57 | 34 | |
| 4,589 | 4,845 | |
| 1.2% | - | |
| 9.1 | 8.9 | |
| 2 days ago | 5 months ago | |
| Bikeshed | Rust | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gpuweb
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Show HN: I built a free in-browser Llama 3 chatbot powered by WebGPU
Works for me.
WebGPU support is behind a couple flags on Linux: https://github.com/gpuweb/gpuweb/wiki/Implementation-Status
- WGSL Is Terrible
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WebGPU now available for testing in Safari Technology Preview
People keep spreading this incredibly misleading statement, and yours is even more misleading (suggesting Apple opposed a 'GPU WASM')
By all accounts, Apple's /only/ stance was that if WebGPU used SPIR-V it would be a non-starter for them, due to ongoing legal issues between Apple and Khronos.
Apple actually proposed WebHLSL in collaboration with Microsoft, to have HLSL be the standard.
Mozilla employee's stance[0] was that SPIRV was too low level, did not fit with the goals of WebGPU portability and security, and expressed concern that Khronos may add functionality to SPIRV they cannot support in WebGPU like raytracing instructions .. 'So we'd always be on the verge of forking SPIR-V in some way.'
It was also noted by many people that even if a bytecode format was used, it would still have to be translated to the target (HLSL/DXIL, MSL, etc.) in almost the same way a text format would.
Nobody proposed a 'GPU WASM equivalent' or an alternative bytecode format.
The hard truth is that shader compilation is a fucking nightmare, people do not realize how bad it is across the different native APIs. SPIR-V is good, but it doesn't solve that - and presents other challenges if you are a web browser API. Vulkan and SPIRV are not the golden goose many make them out to be.
[0] https://github.com/gpuweb/gpuweb/issues/847#issuecomment-642...
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Show HN: WebGPU Particles Simulation
Yes it is still a bit new. WebGPU is not finished and is still being worked on: https://webgpu.io/
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Capturing the WebGPU Ecosystem
WebGPU currently doesn't support the "bindless" resource access model (see: https://github.com/gpuweb/gpuweb/issues/380).
The "max number of sampled texture per shader stage" is a runtime device limit, and the minimal value for that seems to be 16. So texture atlasses are still a thing in WebGPU.
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Why aren't we using highly efficient int8 calcualtions in quants? (maybe eli14?)
There's even an implementation under discussion to have the dp4a instruction added to WebGPU (https://github.com/gpuweb/gpuweb/issues/2677)
- WebGPU – All of the cores, none of the canvas
- How to get Chromium working with the Vulkan driver on a RPi4?
- Anyone has Chromium WebGPU working?
- [Rust_Gamedev] WGSL est-il un bon choix?
burn
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Burn 0.10.0 Released 🔥 (Deep Learning Framework)
Release Note: https://github.com/burn-rs/burn/releases/tag/v0.10.0
- Deep Learning Framework in Rust: Burn 0.10.0 Released
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Why Rust Is the Optimal Choice for Deep Learning, and How to Start Your Journey with the Burn Deep Learning Framework
The comprehensive, open-source deep learning framework in Rust, Burn, has recently undergone significant advancements in its latest release, highlighted by the addition of The Burn Book 🔥. There has never been a better moment to embark on your deep learning journey with Rust, as this book will guide you through your initial project, providing extensive explanations and links to relevant resources.
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Candle: Torch Replacement in Rust
Burn (deep learning framework in rust) has WGPU backend (WebGPU) already. Check it out https://github.com/burn-rs/burn. It was released recently.
- Burn – A Flexible and Comprehensive Deep Learning Framework in Rust
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Announcing Burn-Wgpu: New Deep Learning Cross-Platform GPU Backend
For more details about the latest release see the release notes: https://github.com/burn-rs/burn/releases/tag/v0.8.0.
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Are there any ML crates that would compile to WASM?
Tract is the most well known ML crate in Rust, which I believe can compile to WASM - https://github.com/sonos/tract/. Burn may also be useful - https://github.com/burn-rs/burn.
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Any working wgpu compute example that would run in a browser?
We, the burn team, are working on the wgpu backend (WebGPU) for Burn deep learning framework. You can check out the current state: https://github.com/burn-rs/burn/tree/main/burn-wgpu
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I’ve fallen in love with rust so now what?
Here is the project: https://github.com/burn-rs/burn
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Is anyone doing Machine Learning in Rust?
Disclaimer, I'm the main author of Burn https://burn-rs.github.io.
What are some alternatives?
wgsl.vim - WGSL syntax highlight for vim
candle - Minimalist ML framework for Rust
pyodide - Pyodide is a Python distribution for the browser and Node.js based on WebAssembly
dfdx - Deep learning in Rust, with shape checked tensors and neural networks
noclip.website - A digital museum of video game levels
tch-rs - Rust bindings for the C++ api of PyTorch.
BestBuy-GPU-Bot - BestBuy Bot is an Add to cart and Auto Checkout Bot. This auto buying bot can search the item repeatedly on the ITEM page using one keyword. Once the desired item is available it can add to cart and checkout very fast. This auto purchasing BestBuy Bot can work on Firefox Browser so it can run in all Operating Systems. It can run for multiple items simultaneously.
Graphite - 2D raster & vector editor that melds traditional layers & tools with a modern node-based, non-destructive, procedural workflow.
wgpu-rs - Rust bindings to wgpu native library
tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference [Moved to: https://github.com/sonos/tract]
WASI - WebAssembly System Interface
L2 - l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust