stablehlo
pygfx
| stablehlo | pygfx | |
|---|---|---|
| 5 | 3 | |
| 333 | 357 | |
| 4.2% | 3.9% | |
| 9.8 | 8.8 | |
| 4 days ago | 7 days ago | |
| MLIR | Python | |
| Apache License 2.0 | BSD 2-clause "Simplified" License |
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.
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.
pygfx
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Emerging Rust GUI libraries in a WASM world
https://github.com/kushalkolar/fastplotlib
Alternatively, try pygfx for ThreeJS graphics in Python leveraging wgpu. It works great in Notebooks through notebook-rfb. https://github.com/pygfx/pygfx
If you're adventurous, figure out how to make pygfx work with webgpu via wasm
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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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Extending Python with Rust
Rather than using matplotlib, you could try either pygfx (https://github.com/pygfx/pygfx) or fastplotlib (https://github.com/kushalkolar/fastplotlib) to make higher performance graphics using Python.
However, it won't solve your problem of Python not being fast enough doing the calculations.
What are some alternatives?
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
SHA256-WebGPU - Implementation of sha256 in WGSL
numexpr - Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
wgpu-mm
graphics_wgpu
iree - A retargetable MLIR-based machine learning compiler and runtime toolkit.
vswhere - Locate Visual Studio 2017 and newer installations
SHARK - SHARK - High Performance Machine Learning Distribution
fastplotlib - Next-gen fast plotting library running on WGPU using the pygfx rendering engine
glare-core - C++ code used in various Glare Tech Ltd products
three.py - Python 3D library based on three.js and Modern OpenGL