Overview
ONNX Runtime, maintained by Microsoft, is a cross-platform accelerator for model inference and training. It improves performance through graph optimizations and hardware integrations, enabling efficient execution of models exported from PyTorch, TensorFlow/Keras and classical ML libraries across CPUs, GPUs and other accelerators.
Key features
- Cross-platform support and hardware acceleration for various backends.
- Graph-level transformations and optimizations for better runtime performance.
- Support for both inference and distributed training acceleration.
Use cases
- Production model serving with reduced latency and increased throughput.
- Heterogeneous hardware deployments to optimize cost and performance.
- Large-scale batch inference and preprocessing for ML pipelines.
Technical notes
- Native ONNX ecosystem compatibility and extensive deployment examples to simplify integration.