# Triton Inference Server - Introduction

The Triton Inference Server is an open-source platform designed to deploy and manage AI models across various environments efficiently.

It supports a wide range of machine learning and deep learning frameworks, including TensorFlow, PyTorch, ONNX, OpenVINO, and others, making it versatile for different AI applications.

### <mark style="color:purple;">Key capabilities of Triton Inference Server include</mark>

<mark style="color:green;">**Multi-Framework Support:**</mark>Triton is compatible with numerous AI frameworks, allowing teams to deploy models regardless of the framework they were trained in.

<mark style="color:green;">**Cross-Platform Deployment:**</mark> It can be deployed across various platforms, including cloud, data centers, edge devices, and embedded systems, and supports NVIDIA GPUs, x86 and ARM CPUs, and AWS Inferentia.

<mark style="color:green;">**Optimised Performance:**</mark> Triton offers optimised performance for various query types, such as real-time, batch, ensemble, and audio/video streaming, ensuring efficient resource utilisation.

<mark style="color:green;">**Concurrent Model Execution:**</mark> It enables the simultaneous execution of multiple models, enhancing throughput and reducing latency.

<mark style="color:green;">**Dynamic Batching:**</mark> This feature groups together incoming inference requests for batch processing, improving efficiency and resource utilisation.

<mark style="color:green;">**Sequence Batching and State Management:**</mark> Triton manages stateful models effectively with sequence batching and implicit state management, crucial for applications like time-series analysis.

<mark style="color:green;">**Custom Backends and Pre/Post-Processing:**</mark> The Backend API allows the addition of custom backends and operations, providing flexibility to tailor the server to specific needs.

<mark style="color:green;">**Model Pipelines:**</mark> With ensembling and Business Logic Scripting (BLS), users can create complex model pipelines for advanced inference scenarios.

<mark style="color:green;">**Multiple Inference Protocols:**</mark> Triton supports HTTP/REST and GRPC protocols, making it accessible from various client applications.

<mark style="color:green;">**Monitoring and Metrics:**</mark> It provides detailed metrics on GPU utilization, server throughput, and latency, aiding in performance monitoring and optimization.

Triton Inference Server is part of NVIDIA AI Enterprise, offering a robust platform for developing and deploying AI models at scale.

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