laskin.live
webgpu-blas
| laskin.live | webgpu-blas | |
|---|---|---|
| 2 | 3 | |
| 6 | 97 | |
| - | - | |
| 10.0 | 4.8 | |
| over 3 years ago | 3 months ago | |
| HTML | TypeScript | |
| MIT License | MIT License |
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laskin.live
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Chrome Ships WebGPU
For anyone figuring out how to run webgpu on a remote computer (over webrtc) , see this: https://github.com/periferia-labs/laskin.live
Not sure if it works anymore (I made it 3 years ago), but will be interesting to see if there will be similar products for LLMs and so now.
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WebRTC.rs reached an important milestone in connectivity!
Shameless plug but a friend of mine and I combined both WebRTC and WebGPU some time ago: https://github.com/periferia-labs/laskin.live
webgpu-blas
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Chrome Ships WebGPU
Looks like no -- there appears to be no tensor core or similar support and this SGEMM (fp32 matrix multiply) benchmark gets awful results (my laptop gets 330gflops on this when it should be capable of 13000 gflops).
https://github.com/milhidaka/webgpu-blas
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Modern JavaScript:Everything you missed over the last 10 years(ECMAScript 2020)
I think you will be interested to read this article about the future of data programming in JavaScript (http://benschmidt.org/post/2020-01-15/2020-01-15-webgpu/).
I do think that this kind of thing will be able to be built on top of WebGPU (I saw this experimental POC that did so recently: https://github.com/milhidaka/webgpu-blas). The only issue is that since JavaScript doesn't support operator overloading, the code might be a little less readable.
- JavaScript for Data Science
What are some alternatives?
rivi-loader - Vulkan Compute program loader in Rust
numjs - Like NumPy, in JavaScript
SHA256-WebGPU - Implementation of sha256 in WGSL
Material UI - Ready-to-use foundational React components, free forever. It includes Material UI, which implements Google's Material Design.
wgpu-mm
next-auth - Authentication for the Web.
icpts - TypeScript implementation of iterative closest point (ICP) for point cloud registration
wgpu-py - Next generation GPU API for Python
burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. [Moved to: https://github.com/Tracel-AI/burn]
stablehlo - Backward compatible ML compute opset inspired by HLO/MHLO