opov
shumai
| opov | shumai | |
|---|---|---|
| 1 | 15 | |
| 11 | 1,121 | |
| - | 0.1% | |
| 3.3 | 2.2 | |
| 12 months ago | 10 months ago | |
| JavaScript | TypeScript | |
| - | MIT License |
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opov
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PyTorch Primitives in WebGPU for the Browser
I got nerdsniped and made a small library to test this concept. Might maintain
https://github.com/crubier/opov
shumai
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PyTorch Primitives in WebGPU for the Browser
https://github.com/tensorflow/tfjs/tree/master/tfjs-backend-...
([...], tflite-support, tflite-micro)
From facebookresearch/shumai (a JS tensor library) https://github.com/facebookresearch/shumai/issues/122 :
> It doesn't make sense to support anything besides WebGPU at this point. WASM + SIMD is around 15-20x slower on my machine[1]. Although WebGL is more widely supported today, it doesn't have the compute features needed for efficient modern ML (transformers etc) and will likely be a deprecated backend for other frameworks when WebGPU comes online.
tensorflow rust has a struct.Tensor:
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Why do people curse JS so much, but also say it's better than Python
JS for ML actually does exist https://github.com/facebookresearch/shumai
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Breaking Up with Python
> It's really a shame that data science, ML, and notebooks are so wrapped up in it. Otherwise we could jettison the whole thing into space
Although I personally feel Python has its place, I contribute to a project that hopes to diversify the ML/scientific computing space with a TypeScript tensor lib called Shumai: https://github.com/facebookresearch/shumai
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Tinygrad: A simple and powerful neural network framework
Doesn’t really matter for large batch/large model training on GPUs that don’t need much coordination.
But Python speed is one of the main motivations for a JS/TS based ML lib I’m working on: https://github.com/facebookresearch/shumai
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[D] Using JavaScript for ML Training/Research (not in the browser)
As a hedge against CPython never becoming fast, we're creating a project called Shumai that attempts to deeply integrate with a new JavaScript runtime (Bun[3]).
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Python 3.11 is much faster than 3.8
You can expose objects. Here's how it is done in Bun: https://github.com/facebookresearch/shumai/blob/main/shumai/...
We've been using this feature heavily in Shumai.
I think you are vastly overestimating the complexity associated with this (user exposed ref-counting/garbage collection) and may not be totally up to date on what's implemented.
- Shumai: Fast Differentiable Tensor Library in TypeScript with Bun and Flashlight
- Shumai: A fast differentiable tensor library for research in TypeScript and JavaScript
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7% Speedup from Switch to and
This thought is pretty much the exact motivation behind a recent effort I’m helping out with https://github.com/facebookresearch/shumai
What are some alternatives?
benchmark - TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.
rosettaboy - A gameboy emulator in several different languages
requests-wasm-polyfill - Drop-in replacement for the requests library for wasm python
jittor - Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
potatogpt - Pure Typescript, dependency free, ridiculously slow implementation of GPT2 for educational purposes
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
devdocs - API Documentation Browser
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
FrameworkBenchmarks - Source for the TechEmpower Framework Benchmarks project
llama.cpp - LLM inference in C/C++
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration