openxla/xla
A machine learning compiler for GPUs, CPUs, and ML accelerators
About the project
XLA (Accelerated Linear Algebra) is an open-source ML compiler for GPUs, CPUs, and ML accelerators. It takes models from PyTorch, TensorFlow, and JAX and optimizes them for high-performance execution across different hardware.
Useful for
- Compile a JAX or TensorFlow model for accelerated execution on GPU
- Add support for a new hardware backend to XLA for an ML accelerator
- Debug an ML framework integration with XLA while developing the compiler
README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.
Why it’s trending
- 0 stars so far today, about 1 expected by the end of the day.
- GitHub Trending C++ today: #5, +5 stars.
Stars per day
Bars are daily stars, the line is the usual pace. Red marks spike days.
Numbers
- Total stars
- 4,554
- Today
- 0 · ≈ 1 by evening
- Forks
- 949
- Issues and pull requests
- 49,317
- Watchers
- 49
- Language
- C++
- License
- Apache-2.0
- Created
- August 9, 2022
- Last push
- September 24, 2026
Star trust
Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.
These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.
Spotted in
- September 24, 2026GitHub Trending C++ today: #5, +5 stars
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