Accelerated Linear Algebra

XLA (Accelerated Linear Algebra)
Developer(s)	OpenXLA
Repository	xla on GitHub
Written in	C++
Operating system	Linux, macOS, Windows
Type	compiler
License	Apache License 2.0
Website	openxla.org

XLA (Accelerated Linear Algebra) is an open-source compiler for machine learning developed by the OpenXLA project. ^[1] XLA is designed to improve the performance of machine learning models by optimizing the computation graphs at a lower level, making it particularly useful for large-scale computations and high-performance machine learning models. Key features of XLA include: ^[2]

• Compilation of Computation Graphs: Compiles computation graphs into efficient machine code.
• Optimization Techniques: Applies operation fusion, memory optimization, and other techniques.
• Hardware Support: Optimizes models for various hardware, including CPUs, GPUs, and NPUs.
• Improved Model Execution Time: Aims to reduce machine learning models' execution time for both training and inference.
• Seamless Integration: Can be used with existing machine learning code with minimal changes.

XLA represents a significant step in optimizing machine learning models, providing developers with tools to enhance computational efficiency and performance. ^{[3] [4]}

Supported target devices

• x86-64
• ARM64
• NVIDIA GPU
• AMD GPU
• Intel GPU ^[5]
• Apple GPU ^[6]
• Google TPU
• AWS Trainium, Inferentia ^[7]
• Cerebras ^[8]
• Graphcore IPU ^[9]

See also

• TensorFlow
• PyTorch ^[10]
• JAX

References

1. "OpenXLA Project" . Retrieved December 21, 2024.
2. Woodie, Alex (2023-03-09). "OpenXLA Delivers Flexibility for ML Apps". Datanami. Retrieved 2023-12-10.
3. "TensorFlow XLA: Accelerated Linear Algebra". TensorFlow Official Documentation. Retrieved 2023-12-10.
4. Smith, John (2022-07-15). "Optimizing TensorFlow Models with XLA". Journal of Machine Learning Research. 23: 45–60.
5. "intel/intel-extension-for-openxla". GitHub . Retrieved December 29, 2024.
6. "Accelerated JAX on Mac - Metal - Apple Developer" . Retrieved December 29, 2024.
7. "Developer Guide for Training with PyTorch NeuronX — AWS Neuron Documentation". awsdocs-neuron.readthedocs-hosted.com. Retrieved 29 December 2024.
8. Barsoum, Emad (13 April 2022). "Supporting PyTorch on the Cerebras Wafer-Scale Engine - Cerebras". Cerebras. Retrieved 29 December 2024.
9. Ltd, Graphcore. "Poplar® Software". graphcore.ai. Retrieved 29 December 2024.
10. "PyTorch/XLA documentation — PyTorch/XLA master documentation". pytorch.org. Retrieved 29 December 2024.