Skip to content

Evaluation plan

Baselines

Baseline Stands in for
random sanity floor
reactive_fastest SpotServe / Petals style: fastest feasible node, recover after failure
load-aware (todo) Llumnix-style queue balancing
replica hedging (todo) SkyServe SpotHedge
prefix-cache-aware (todo) llm-d default scorer
oracle upper bound: knows true remaining session length

Metrics

Goodput under SLO; TTFT; TPOT / ITL; P50, P90, P99 latency; SLO attainment; wasted GPU-seconds (recompute + lost work); $/token relative to on-demand; planned and unplanned migration counts and downtime; fraction of requests hit by unplanned loss.

Traces

Cross one availability trace with one workload trace. See traces/README.md for sources and licences (SpotLake, Google 2019, Failure Trace Archive, SETI@home/BOINC; Azure LLM Inference 2023, BurstGPT, Mooncake).

Ablations

Hazard estimator family (KM / Weibull / hierarchical / boosted with features) × migration trigger parameters × output-length estimate noise × workload mix.

Simulator validation

Record real churn on a small spot cluster and a few consumer machines (Phase 4), replay it through the simulator, and publish the fidelity plot. Prior art did the same on 12× g4dn (SpotServe) and g6/g6e (ShuntServe).