Introduction
Dynamo (NVIDIA) is an open-source framework for datacenter-scale inference, addressing orchestration challenges in multi-GPU and multi-node deployments. It is engine-agnostic and supports backends like vLLM, SGLang, and TensorRT-LLM, focusing on throughput, latency, and efficient KV cache management.
Key Features
- Supports multiple inference engines and deployment topologies
- Disaggregated prefill & decode strategies for throughput/latency tradeoffs
- KV-aware routing and cache offloading for higher system throughput
- Deployment guides and benchmarking tools for production readiness
Use Cases
- Large-scale online LLM serving across multiple GPUs/nodes
- Performance-sensitive scenarios requiring fine-grained scheduling
- Benchmarking and evaluating inference architectures
Technical Highlights
- Core implemented in Rust for performance, with Python tooling and extensibility
- Depends on etcd and NATS for coordination and discovery
- Rich engine adapters and examples for Kubernetes and local testing