T0 + T1 + T2: engine redesign through new API surface #1

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logaritmisk merged 45 commits from t2-new-api-surface into main 2026-04-24 11:20:04 +00:00
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@@ -5,8 +5,39 @@
Batch::iteration 29.840 µs
Gaussian::add 219.58 ps
Gaussian::sub 219.41 ps
Gaussian::mul 1.568 ns
Gaussian::div 1.572 ns
Gaussian::mul 1.568 ns ← hot path; target ≥1.5× improvement
Gaussian::div 1.572 ns ← hot path; target ≥1.5× improvement
Gaussian::pi 262.89 ps
Gaussian::tau 262.47 ps
Gaussian::pi_tau_combined 219.40 ps
# After T0 (2026-04-24, same hardware)
Batch::iteration 21.253 µs (1.40× — below 3× target; see post-mortem)
Gaussian::add 218.62 ps (1.00× — unchanged, Add/Sub use moment form)
Gaussian::sub 220.15 ps (1.00×)
Gaussian::mul 218.69 ps (7.17× — nat-param: now two f64 adds, no sqrt)
Gaussian::div 218.64 ps (7.19× — nat-param: now two f64 subs, no sqrt)
Gaussian::pi 263.19 ps (1.00× — now a field read, same cost)
Gaussian::tau 263.51 ps (1.00× — now a field read, same cost)
Gaussian::pi_tau_combined 219.13 ps (1.00×)
# Post-mortem: Batch::iteration 1.40× vs. 3× target
#
# Root cause: the bench has 100 tiny 2-team events. Each event still allocates
# ~10 Vecs per iteration (down from ~18). The arena covers teams/diffs/ties/margins
# (was 4 Vecs, now 0 new allocs) but the following remain:
# - within_priors() returns Vec<Vec<Player<D>>>: 3 Vecs per event (300 total)
# - event.outputs() returns Vec<f64>: 1 Vec per event (100 total)
# - sort_perm() allocates 2 scratch Vecs: 200 total
# - Game::likelihoods = collect() allocates Vec<Vec<Gaussian>>: 4 Vecs (400 total)
# Total remaining: ~1000 allocs per iteration call vs. ~1800 before (44% reduction).
#
# The HashMap → dense Vec win (target 24×) benefits the History-level forward/backward
# sweep, NOT Batch::iteration in isolation — so this bench doesn't show it.
#
# To hit ≥3× on Batch::iteration:
# - Arena-ify sort_perm (use a stack-fixed array for small n_teams)
# - Pass a within_priors output buffer through the arena
# - Make Game::likelihoods write into an arena slice rather than allocating
# These land in T1 (factor graph) when we redesign Game's internals.