Why architecture matters here
HPO fails on wasted compute (no early stopping), poor search space (too wide or narrow), and lack of reproducibility. Architecture matters because ASHA + BO + warm-start make HPO efficient.
The architecture: every piece explained
The top strip is the loop. Search space defines parameters + ranges. Suggester — BO/TPE/random. Trial runner trains + evaluates. Early stopping — ASHA or HyperBand.
The middle row is efficiency. Parallelism across GPUs. Objective + noise — pick metric aware of variance. Warm starting transfers priors from past runs. Multi-objective — cost + quality Pareto.
The lower rows are ops. Results storage in tracker. Metrics — regret + budget used. Ops — governance + reproducibility + best-config export.
End-to-end flow
End-to-end: HPO study defined. 100 trials budget. TPE suggester + ASHA. Parallelism 8 GPUs. Trials run; poor ones killed early. Best config beats baseline by 3%. Warm-start next study from these results. Best config exported to registry.