wehub-resource-sync
50 lines
1.6 KiB
Markdown
50 lines
1.6 KiB
Markdown
# XLA
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XLA (Accelerated Linear Algebra) is an open-source machine learning (ML)
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compiler for GPUs, CPUs, and ML accelerators.
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="docs/images/openxla_dark.svg">
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<img alt="OpenXLA Ecosystem" src="docs/images/openxla.svg">
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</picture>
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The XLA compiler takes models from popular ML frameworks such as PyTorch,
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TensorFlow, and JAX, and optimizes them for high-performance execution across
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different hardware platforms including GPUs, CPUs, and ML accelerators.
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[openxla.org](https://openxla.org/) is the project's website.
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## Get started
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If you want to use XLA to compile your ML project, refer to the corresponding
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documentation for your ML framework:
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* [PyTorch](https://pytorch.org/xla)
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* [TensorFlow](https://www.tensorflow.org/xla)
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* [JAX](https://jax.readthedocs.io/en/latest/notebooks/quickstart.html)
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If you're not contributing code to the XLA compiler, you don't need to clone and
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build this repo. Everything here is intended for XLA contributors who want to
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develop the compiler and XLA integrators who want to debug or add support for ML
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frontends and hardware backends.
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## Contribute
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If you'd like to contribute to XLA, review
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[How to Contribute](docs/contributing.md) and then see the
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[developer guide](docs/developer_guide.md).
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## Contacts
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* For questions, contact the maintainers - maintainers at openxla.org
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## Resources
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* [Community Resources](https://github.com/openxla/community)
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## Code of Conduct
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While under TensorFlow governance, all community spaces for SIG OpenXLA are
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subject to the
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[TensorFlow Code of Conduct](https://github.com/tensorflow/tensorflow/blob/master/CODE_OF_CONDUCT.md).
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