Async coverage was incomplete in 0.7 (only RandomSearch and
DifferentialEvolution had run_async). 0.8 closes the gap: every one
of the 33 algorithms now exposes
run_async(&problem, concurrency).await, gated on the async feature.
- Population-based algorithms fan out per-generation evaluations
through evaluate_batch_async with concurrency-bounded
FuturesOrdered chunks.
- Steady-state algorithms (HillClimber, SimulatedAnnealing,
OnePlusOneEs, Paes, NelderMead) await each step sequentially;
they accept the concurrency parameter for API uniformity.
- TabuSearch fans out the K-neighbor batch each step.
- Surrogate algorithms (BayesianOpt, Tpe) batch the initial design
and await per-iteration acquisitions sequentially so the surrogate
can update between picks.
- Hyperband uses a new AsyncPartialProblem trait (mirroring
PartialProblem for multi-fidelity workloads) and a parallel
evaluate_batch_at_budget_async helper; each Successive-Halving
rung fans out its budgeted evaluations.
All paths preserve seeded determinism: RNG draws happen on the main
task in the same order as the sync path, and only the evaluations
are concurrent.
Adds a dedicated cookbook recipe at docs/book/src/cookbook/async.md
with a worked example (DifferentialEvolution under tokio) and
guidance on picking concurrency. Cross-references in SUMMARY.md
and cookbook.md are updated to surface the new recipe.
The follow-up docs commit reconciles the rest of the user guide
and README to describe the new feature; this commit is the bare
async surface.
swaits
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