Déploiement

Triton Inference Server

Définition

NVIDIA's open-source inference serving software that supports multiple frameworks (TensorRT, ONNX, PyTorch, TensorFlow) on GPU infrastructure. Triton is widely used in enterprise deployments requiring maximum throughput from GPU hardware.

Termes Connexes

ONNX (Open Neural Network Exchange)

An open format for representing machine learning models that enables interoperability across frameworks and hardware. Exporting to ONNX allows models trained in PyTorch to run efficiently on TensorRT, OpenVINO, or other optimised runtimes.

Model Serving

The process of deploying trained ML models to production environments where they can receive inputs and return predictions at scale. Model serving infrastructure must address throughput, latency, versioning, and cost while meeting SLAs.

Ray Serve

An open-source, scalable model serving framework built on the Ray distributed computing library. Ray Serve supports complex inference pipelines with model composition, dynamic batching, and Python-native deployment, making it popular for LLM serving.

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