For AI agents: a documentation index is available at the root level at /llms.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
This page is for version v0.8.1.
For other versions, use one of these documentation indexes:
- Latest (v1.5.1) (default): https://docs.nvidia.com/dynamo/latest/llms.txt
- dev: https://docs.nvidia.com/dynamo/dev/llms.txt
- v1.5.1: https://docs.nvidia.com/dynamo/v1.5.1/llms.txt
- v1.5.0: https://docs.nvidia.com/dynamo/v1.5.0/llms.txt
- v1.4.2: https://docs.nvidia.com/dynamo/v1.4.2/llms.txt
- v1.4.1: https://docs.nvidia.com/dynamo/v1.4.1/llms.txt
- v1.4.0: https://docs.nvidia.com/dynamo/v1.4.0/llms.txt
- v1.3.0: https://docs.nvidia.com/dynamo/v1.3.0/llms.txt
- v1.2.1: https://docs.nvidia.com/dynamo/v1.2.1/llms.txt
- v1.2.0: https://docs.nvidia.com/dynamo/v1.2.0/llms.txt
- v1.1.1: https://docs.nvidia.com/dynamo/v1.1.1/llms.txt
- v1.1.0: https://docs.nvidia.com/dynamo/v1.1.0/llms.txt
- v1.0.2: https://docs.nvidia.com/dynamo/v1.0.2/llms.txt
- v1.0.1: https://docs.nvidia.com/dynamo/v1.0.1/llms.txt
- v1.0.0: https://docs.nvidia.com/dynamo/v1.0.0/llms.txt
- v0.9.1: https://docs.nvidia.com/dynamo/v-0-9-1/llms.txt
- v0.9.0: https://docs.nvidia.com/dynamo/v-0-9-0/llms.txt
- v0.8.1: https://docs.nvidia.com/dynamo/v-0-8-1/llms.txt
- v0.8.0: https://docs.nvidia.com/dynamo/v-0-8-0/llms.txt
- v0.7.1: https://docs.nvidia.com/dynamo/v-0-7-1/llms.txt
- v0.7.0: https://docs.nvidia.com/dynamo/v-0-7-0/llms.txt
KVBM Integrates with Inference frameworks (vLLM, TRTLLM, SGLang) via Connector APIs to influence KV caching behaviour, scheduling, and forward pass execution.
There are two components of the interface, Scheduler and Worker. Scheduler(leader) is responsible for the orchestration of KV block offload/onboard, builds metadata specifying transfer data to the workers. It also maintains hooks for handling asynchronous transfer completion. Worker is responsible for reading metadata built by the scheduler(leader), does async onboarding/ offloading at the end of the forward pass.
Typical KVBM Integrations
The following figure shows the typical integration of KVBM with inference frameworks (vLLM used as an example)