Unleash Lightning-Fast AI: A Deep Dive into NVIDIA Dynamo for LLM Serving

Tired of sluggish inference speeds for your Generative AI and reasoning models? NVIDIA Dynamo is here to revolutionize your multi-node, distributed environments. This open-source framework delivers high-throughput, low-latency inference, so you can serve complex models with unparalleled speed.

What is NVIDIA Dynamo? The Inference Engine Agnostic Framework

Dynamo is a game-changing inference framework specifically designed for large language models (LLMs). Unlike other solutions, it's inference engine agnostic – meaning it seamlessly integrates with your preferred engines like TRT-LLM, vLLM, and SGLang. The beauty of NVIDIA Dynamo lies in its ability to capture key LLM capabilities, optimizing performance at every step.

Supercharge Your LLM Performance: Key Features & Benefits

Dynamo optimizes your LLM performance using:

• Disaggregated prefill & decode inference: Maximizes GPU throughput, enabling a customizable balance between speed and low latency.
• Dynamic GPU scheduling: Intelligently adapts to fluctuating demand, ensuring consistent performance.
• LLM-aware request routing: Eliminates redundant KV cache re-computation, improving efficiency.
• Accelerated data transfer (NIXL): Reduces inference response time for a more responsive experience.
• KV cache offloading: Leverages diverse memory tiers for increased throughput.

Get Started with NVIDIA Dynamo: Installation Guide

Ready to experience the power of NVIDIA Dynamo? Follow these simple installation steps:

1. System Requirements: Recommended to use Ubuntu 24.04 with a x86_64 CPU.

2. Install System Packages:

   apt-get update
   DEBIAN_FRONTEND=noninteractive apt-get install -yq python3-dev python3-pip python3-venv libucx0
   

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3. Create a Virtual Environment:

   python3 -m venv venv
   source venv/bin/activate
   

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4. Install the ai-dynamo Package:

   pip install ai-dynamo[all]
   

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Deploying with Docker: Building Your Dynamo Base Image

For Kubernetes deployments, you'll need to build and push a Dynamo base image to your container registry (Docker Hub, NVIDIA NGC, or your private registry).

1. Build the Image:

   ./container/build.sh
   docker tag dynamo:latest-vllm <your-registry>/dynamo-base:latest-vllm
   docker login <your-registry>
   docker push <your-registry>/dynamo-base:latest-vllm
   

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2. Set the Environment Variable:

   export DYNAMO_IMAGE=<your-registry>/dynamo-base:latest-vllm
   

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Run LLMs Locally: A Quick Start Guide

Test NVIDIA Dynamo locally with a Hugging Face model:

dynamo run out=vllm deepseek-ai/DeepSeek-R1-Distill-Llama-8B

LLM Serving Made Easy: Distributed Runtime Services

Dynamo simplifies LLM serving with these components:

• OpenAI Compatible Frontend: A high-performance HTTP API server written in Rust.
• Basic and KV Aware Router: Routes and load balances traffic.
• Workers: Pre-configured LLM serving engines.

Boost Your Model Serving with NVIDIA Dynamo

NVIDIA Dynamo's disaggregated prefill & decode inference, combined with dynamic GPU scheduling, accelerates data transfer, optimizes KV cache, and ultimately reduces latency. It also accelerates your model serving. Start leveraging Dynamo today and unlock a new level of performance for your generative AI applications.