A rigorous A/B benchmark of NVIDIA Dynamo's KV-aware router vs round-robin routing, on identical multi-worker aggregated deployments, driven by a real production trace (Mooncake) and profiled with a custom observability stack (inferscope) on top of NVIDIA's own AIPerf methodology.
- Method: two deployments differing ONLY in
--router-mode(round-robin vs kv), same worker count, deterministic KV hashing, warm-up + 3 averaged runs. - Workload: Mooncake arxiv trace (real shared-prefix structure; the case where KV routing matters). Filtered to inputs <= 16384 tokens (89.7% of the trace).
- Measurement: AIPerf for client-side latency/throughput; inferscope
--sample-onlyfor server-side per-device GPU truth (SM/VRAM/power) that the NVIDIA A/B guide does not show. - Triangulation: AIConfigurator predicted vs AIPerf measured vs inferscope resource-observed.
Cold preparation complete (see RUNBOOK.md). Execution pending on a rented multi-GPU instance. This repo holds the runbook, the A/B launch scripts, and (once run) the analysis.
RUNBOOK.md— the full end-to-end procedure, phase by phase.scripts/arm_common.sh— shared launcher; router mode is the single A/B variable.scripts/arm_off.sh,scripts/arm_on.sh— the two arms (round-robin vs kv).