Run Cluster Validation Suite (CVS) inference and benchmarking test suites#
2026-10-21
3 min read time
LLM serving, disaggregated prefill/decode, and diffusion workloads for cluster-scale inference validation.
See also Run Cluster Validation Suite (CVS) test suites on AMD Instinct GPU clusters for common cvs run flags and workflow.
Common prerequisites#
These prerequisites apply to every inference suite. Each suite page lists only its additional requirements.
On every GPU node:
Docker, with the SSH user able to run it through passwordless
sudo dockeror membership in thedockergroup.The host ROCm driver loaded, so
/dev/kfd,/dev/dri/*, and/dev/infiniband/*when the workload uses RDMA are available for device passthrough.The suite container image loaded on the node or pullable from a reachable registry.
Model weights on storage mounted at the same path on every participating node.
A Hugging Face token file when the model requires gated access.
On the machine where you run cvs run:
CVS installed (see Install Cluster Validation Suite (CVS) on ROCm).
SSH key access to every cluster node.
Test results#
Sample output snapshots from inference and diffusion runs.
Important
The numbers in these sample reports and screenshots (throughput, latency, and every other metric) are illustrative sample values, not final tuned results. They are shown only to illustrate the report layout.
Inference#
HTML test report#
Run Deck report#
The Run Deck dashboard: run card, lifecycle timeline, sweep cells, cross-shape comparison, and full results.
Run Deck interactive viewer#
The interactive viewer: token throughput per GPU versus interactivity, and gate margin versus concurrency.
Diffusion#
HTML test report#
Run Deck report#
The Run Deck dashboard: run card and full results.