stablehlo
wgpu-py
stablehlo | wgpu-py | |
---|---|---|
5 | 5 | |
333 | 371 | |
4.2% | 2.7% | |
9.8 | 8.6 | |
4 days ago | 6 days ago | |
MLIR | Python | |
Apache License 2.0 | BSD 2-clause "Simplified" License |
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stablehlo
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Nvidia H200 Tensor Core GPU
I am going to paste a cousin comment:
StableHLO[1] is an interesting project that might help AMD here:
> Our goal is to simplify and accelerate ML development by creating more interoperability between various ML frameworks (such as TensorFlow, JAX and PyTorch) and ML compilers (such as XLA and IREE).
From there, their goal would most likely be to work with XLA/OpenXLA teams on XLA[3] and IREE[2] to make RoCM a better backend.
[1] https://github.com/openxla/stablehlo
[2] https://github.com/openxla/iree
[3] https://www.tensorflow.org/xla
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Chrome Ships WebGPU
Also see the recently introduced StableHLO and its serialization format: https://github.com/openxla/stablehlo/blob/main/docs/bytecode...
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OpenXLA Is Available Now
If you mean StableHLO, then it has an MLIR dialect: https://github.com/openxla/stablehlo/blob/main/stablehlo/dia....
In the StableHLO spec, we are talking about this in more abstract terms - "StableHLO opset" - to be able to unambiguously reason about the semantics of StableHLO programs. However, in practice the StableHLO dialect is the primary implementation of the opset at the moment.
I wrote "primary implementation" because e.g. there is also ongoing work on adding StableHLO support to the TFLite flatbuffer schema: https://github.com/tensorflow/tensorflow/blob/master/tensorf.... Having an abstract notion of the StableHLO opset enables us to have a source of truth that all the implementations correspond to.
wgpu-py
- Pygfx/wgpu-py: Next generation GPU API for Python
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I'm working on techno audio-visuals using Ableton & Javascript
If you've a Python background, I might suggest checking out something like https://github.com/pygfx/wgpu-py
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Chrome Ships WebGPU
FYI you can already use webgpu directly in python, see https://github.com/pygfx/wgpu-py for webgpu wrappers and https://github.com/pygfx/pygfx for a more high level graphics library
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I've just started mixing shaders with Pygame and got some great results
This reminds me of another Python GPU project, bringing in WebGPU shaders.
https://github.com/pygfx/wgpu-py
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Unifying the CUDA Python Ecosystem
Somewhat related, I’ve built compute shaders using wgpu-py:
https://github.com/pygfx/wgpu-py
You can define any compute shader you like in Python, with the data types, and it compiles it to SPIRV and runs it.
What are some alternatives?
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
CudaPy - CudaPy is a runtime library that lets Python programmers access NVIDIA's CUDA parallel computation API.
SHA256-WebGPU - Implementation of sha256 in WGSL
cudf - cuDF - GPU DataFrame Library
wgpu-mm
iree - A retargetable MLIR-based machine learning compiler and runtime toolkit.
grcuda - Polyglot CUDA integration for the GraalVM
SHARK - SHARK - High Performance Machine Learning Distribution
web-stable-diffusion - Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
glare-core - C++ code used in various Glare Tech Ltd products
copperhead - Data Parallel Python