dynamo.nixl_connect.RdmaMetadata — Dynamo
Title: dynamo.nixl_connect.RdmaMetadata — Dynamo
Published Time: Fri, 22 Aug 2025 17:35:02 GMT
Markdown Content: Skip to main content
Back to top- [x] - [x]
Ctrl+K
Search Ctrl+K
Search Ctrl+K
Table of Contents
Architecture & Features
Using Dynamo
- Writing Python Workers in Dynamo
- Disaggregation and Performance Tuning
- Working with Dynamo Kubernetes Operator
Deployment Guides
- Dynamo Deploy Quickstart
- Dynamo Cloud Kubernetes Platform
- Manual Helm Deployment
- Minikube Setup Guide
- Model Caching with Fluid
Examples
- Hello World
- LLM Deployment Examples using VLLM
- LLM Deployment Examples using SGLang
- Multinode Examples using SGLang
- Planner Benchmark Example
- LLM Deployment Examples using TensorRT-LLM
Reference
-
dynamo.nixl_...
dynamo.nixl_connect.RdmaMetadata#
A Pydantic type intended to provide JSON serialized RDMA metadata about a ReadableOperation or WritableOperation object. RDMA metadata contains detailed information about a worker process and how to access memory descriptors registered with it. This data is required to perform data transfers using the NIXL based RDMA subsystem.
Warning
RDMA metadata contains a worker’s address as well as security keys to access specific registered memory descriptors. This data provides direct memory access between workers, and should be considered sensitive and therefore handled accordingly.
Use the respective class’s .metadata() method to generate an RdmaMetadata object for an operation.
Tip
Classes using RdmaMetadata objects must be paired correctly. ReadableOperation with ReadOperation, and WritableOperation with WriteOperation. Incorrect pairing will result in an error being raised.
Related Classes#
On this page
Privacy Policy | Manage My Privacy | Do Not Sell or Share My Data | Terms of Service | Accessibility | Corporate Policies | Product Security | Contact
Copyright © 2025-2025, NVIDIA Corporation.
Links/Buttons:
- Skip to main content
- document.write(
<img src="../../_static/nvidia-logo-horiz-rgb-wht-for-screen.svg" class="logo__image only-dark" alt="Dynamo - Home"/>); Dynamo - GitHub
- Support Matrix
- High Level Architecture
- Distributed Runtime
- Disaggregated Serving
- KV Block Manager
- Motivation
- KVBM Architecture
- Understanding KVBM components
- KVBM Further Reading
- KV Cache Routing
- Planner
- Pre-Deployment Profiling
- Load-based Planner
- SLA-based Planner
- Dynamo Architecture Flow
- Writing Python Workers in Dynamo
- Disaggregation and Performance Tuning
- Working with Dynamo Kubernetes Operator
- Dynamo Deploy Quickstart
- Dynamo Cloud Kubernetes Platform
- Manual Helm Deployment
- Minikube Setup Guide
- Model Caching with Fluid
- Hello World
- LLM Deployment Examples using VLLM
- LLM Deployment Examples using SGLang
- Multinode Examples using SGLang
- Planner Benchmark Example
- LLM Deployment Examples using TensorRT-LLM
- Glossary
- NIXL Connect API
- #
- ReadableOperation
- WritableOperation
- ReadOperation
- Connector
- Descriptor
- Device
- OperationStatus
- Privacy Policy
- Manage My Privacy
- Do Not Sell or Share My Data
- Terms of Service
- Accessibility
- Corporate Policies
- Product Security
- Contact