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.
Key capabilities of Triton Inference Server include
Multi-Framework Support:Triton is compatible with numerous AI frameworks, allowing teams to deploy models regardless of the framework they were trained in.
Cross-Platform Deployment: 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.
Optimised Performance: Triton offers optimised performance for various query types, such as real-time, batch, ensemble, and audio/video streaming, ensuring efficient resource utilisation.
Concurrent Model Execution: It enables the simultaneous execution of multiple models, enhancing throughput and reducing latency.
Dynamic Batching: This feature groups together incoming inference requests for batch processing, improving efficiency and resource utilisation.
Sequence Batching and State Management: Triton manages stateful models effectively with sequence batching and implicit state management, crucial for applications like time-series analysis.
Custom Backends and Pre/Post-Processing: The Backend API allows the addition of custom backends and operations, providing flexibility to tailor the server to specific needs.
Model Pipelines: With ensembling and Business Logic Scripting (BLS), users can create complex model pipelines for advanced inference scenarios.
Multiple Inference Protocols: Triton supports HTTP/REST and GRPC protocols, making it accessible from various client applications.
Monitoring and Metrics: 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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