clay-borg/games/ground/benches/synthetic.rs
tegwick eb1378e667 T08 complete: benchmarks, determinism evidence, and one missed metric
evidence/CB-EV-0001-game-kernel.md records the acceptance run against
the CB-RES-0001 baseline.

Met: AM-1 rule coverage 58/58; AM-6 throughput 1.65M events/s against a
100k target; AM-7 scaling 1.08x at 20x workload and a 100k-event replay
in 4.13ms against a 5s budget; AM-8 zero divergence over 10 full runs
with fmt and clippy clean; AM-10 zero foreign collection types.

Not met and reported as such: AM-4 at 33 transitive crates against a
<=20 target. Attribution is in the evidence file. The recommended fix
is making serde_yaml optional (-5, a test-only concern), after which
the remainder is sha2 and rand_chacha, which K5 and K7 require. We are
not hand-rolling crypto primitives to win a dependency count.

AM-12 is recorded as uncomputable: per-task token counts were never
instrumented, and inventing a USD figure would defeat the metric.

A measurement error was found and corrected before publication. The
first benchmark reported 9.3M events/s on a flat curve. The workload
had a player selecting SUPPORT while parked at Stress 4, so GR-R03
rejected it, rounds never completed, and throughput was computed for
rounds that never happened. The bench now asserts the per-round event
count and panics rather than measuring a stalled loop. The corrected
figure is 5.6x lower.

The evidence file states plainly what the boardgame.io comparison does
and does not support: the ~450x command-rate ratio is cross-runtime and
cross-feature-set, so it is a direction, not a verdict, per the
InnerLoop parity-cap rule.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-07-31 03:09:14 +02:00

220 lines
8 KiB
Rust

//! AM-6/AM-7 benchmarks (GameKernel §4): the real GROUND aggregate under
//! the CB-RES-0001 synthetic workload (3-player commit/reveal rounds).
//!
//! The baseline is boardgame.io, recorded in
//! research/CB-RES-0001-harness/boardgame-io/results-260731.json. That
//! harness measured moves/second *while history grew*, and its headline
//! finding was that throughput halved as history doubled. AM-7 exists
//! because of that finding, so the same workload sizes are run here:
//! what matters is the shape of the curve, not only the peak number.
use cb_events::state_hash_hex;
use cb_game_runtime::{ScenarioGame, Setup};
use cb_kernel::{Actor, Aggregate, PlayerId};
use criterion::{criterion_group, criterion_main, BatchSize, Criterion, Throughput};
use games_ground::{Action, GroundCommand, GroundMode, GroundState};
use std::collections::BTreeMap;
fn setup(seed: u64) -> GroundState {
GroundState::setup(
&Setup {
players: 3,
preset: "standard-3p".to_string(),
patch: BTreeMap::new(),
},
seed,
)
.expect("standard-3p setup")
}
fn apply(state: &mut GroundState, actor: Actor, command: &GroundCommand) -> usize {
match state.validate(actor, command) {
Ok(events) => {
for event in &events {
state.fold(event);
}
events.len()
}
Err(_) => 0,
}
}
/// One full round for three players: three Selects, Reveal, the GROUND
/// mode choice, Resolve, End. Returns the number of events applied.
fn play_round(state: &mut GroundState) -> usize {
let picks = [
(
PlayerId(0),
GroundCommand::SelectAction {
action: Action::Attack,
target: Some(PlayerId(1)),
problem: None,
},
),
(
PlayerId(2),
GroundCommand::SelectAction {
action: Action::Support,
target: Some(PlayerId(1)),
problem: None,
},
),
(
PlayerId(1),
GroundCommand::SelectAction {
action: Action::Ground,
target: None,
problem: None,
},
),
];
let mut applied = 0;
for (seat, command) in picks {
applied += apply(state, Actor::Player(seat), &command);
}
applied += apply(state, Actor::System, &GroundCommand::Reveal);
// GR-R05: the GROUND player picks a mode before resolution.
applied += apply(
state,
Actor::Player(PlayerId(1)),
&GroundCommand::ChooseGroundMode {
mode: GroundMode::Gr,
choice: None,
},
);
applied += apply(state, Actor::System, &GroundCommand::Resolve);
applied += apply(state, Actor::System, &GroundCommand::EndRound);
applied
}
/// A game ends after Round 5 (GR-R09), so a long run starts a fresh game
/// rather than idling on a finished one. Setup cost is therefore part of
/// the measurement, at one setup per five rounds.
fn run_rounds(rounds: usize) -> usize {
let mut applied = 0;
let mut state = setup(42);
for round in 0..rounds {
if state.outcome.is_some() {
state = setup(42 + round as u64);
}
let produced = play_round(&mut state);
// A workload whose commands get rejected still "runs", but it
// measures nothing. An earlier version of this bench stalled on
// the GR-R03 stress gate and reported throughput for rounds that
// never happened, so refuse to measure that.
assert!(
produced == EVENTS_PER_ROUND || produced == FINAL_ROUND_EVENTS,
"round {round} produced {produced} events, expected {EVENTS_PER_ROUND} \
(or {FINAL_ROUND_EVENTS} on a game's last round)"
);
applied += produced;
}
applied
}
/// Pinned by the `bench_shape` test in the aggregate crate.
const EVENTS_PER_ROUND: usize = 13;
/// GR-R09: a game's fifth round emits GameEnded instead of RoundEnded
/// plus StepAdvanced, so it is one event shorter.
const FINAL_ROUND_EVENTS: usize = 12;
/// Mean events per round over a 5-round game, scaled by 5 to stay in
/// integers: (4 x 13 + 12) = 64.
const EVENTS_PER_5_ROUNDS: usize = 64;
fn bench_synthetic(c: &mut Criterion) {
// Events per round is fixed by the workload, so throughput can be
// reported in events/second — the AM-6 unit.
assert_eq!(play_round(&mut setup(1)), EVENTS_PER_ROUND);
let mut group = c.benchmark_group("synthetic-ground-3p");
// AM-6 headline throughput and AM-7 scaling, at the sizes the
// boardgame.io harness used so the curves line up.
for &rounds in &[5_000usize, 10_000, 20_000, 40_000, 100_000] {
group.throughput(Throughput::Elements(
(rounds * EVENTS_PER_5_ROUNDS / 5) as u64,
));
group.bench_function(format!("rounds-{rounds}"), |b| {
b.iter_batched(|| rounds, run_rounds, BatchSize::SmallInput)
});
}
group.finish();
// AM-7 replay, and the honest analogue of the boardgame.io finding:
// a *single* growing event log folded back into state. The round
// benches above restart the game every 5 rounds (GR-R09), so their
// flat curve is partly by construction — this one is not, because
// the log here grows without bound.
let mut replay = c.benchmark_group("replay-ground-3p");
for &events in &[10_000usize, 100_000] {
replay.throughput(Throughput::Elements(events as u64));
replay.bench_function(format!("fold-{events}-events"), |b| {
// Build one log of `events` events, then measure folding it.
let mut source = setup(42);
let mut log = Vec::with_capacity(events);
while log.len() < events {
if source.outcome.is_some() {
source = setup(43);
}
let picks = [
(
PlayerId(0),
GroundCommand::SelectAction {
action: Action::Attack,
target: Some(PlayerId(1)),
problem: None,
},
),
(
PlayerId(1),
GroundCommand::SelectAction {
action: Action::Support,
target: Some(PlayerId(2)),
problem: None,
},
),
];
for (seat, cmd) in picks {
if let Ok(produced) = source.validate(Actor::Player(seat), &cmd) {
for e in &produced {
source.fold(e);
log.push(e.clone());
}
}
}
if let Ok(produced) = source.validate(Actor::System, &GroundCommand::Reveal) {
for e in &produced {
source.fold(e);
log.push(e.clone());
}
}
if let Ok(produced) = source.validate(Actor::System, &GroundCommand::EndRound) {
for e in &produced {
source.fold(e);
log.push(e.clone());
}
}
}
b.iter(|| {
let mut state = setup(42);
for event in &log {
state.fold(event);
}
state_hash_hex(&state)
})
});
}
replay.finish();
// AM-7: hashing the full aggregate, the per-round determinism cost.
let mut hashing = c.benchmark_group("state-hash-ground-3p");
hashing.throughput(Throughput::Elements(1));
hashing.bench_function("hash-one-state", |b| {
let state = setup(42);
b.iter(|| state_hash_hex(&state))
});
hashing.finish();
}
criterion_group!(benches, bench_synthetic);
criterion_main!(benches);