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smarm/benches/baseline-output/sweep/ai64_tc150k.txt
Bench 3da6ffaa77 benches: expose preemption knobs + sweep runner 
Config API changes (src/preempt.rs, src/runtime.rs):
- preempt: promote ALLOC_INTERVAL and TIMESLICE_CYCLES from bare consts to
  DEFAULT_ALLOC_INTERVAL / DEFAULT_TIMESLICE_CYCLES; store active values in
  thread-locals set on each actor resume so multiple runtimes can use
  different settings concurrently.
- runtime: add alloc_interval / timeslice_cycles fields to Config; add
  Config::alloc_interval(n) and Config::timeslice_cycles(c) builder methods;
  thread the values through RuntimeInner to the reset_timeslice() call in
  schedule_loop.

Bench changes:
- Add bench_cfg(threads) helper to general/tokio_favored/smarm_favored that
  wraps Config::exact and reads SMARM_ALLOC_INTERVAL / SMARM_TIMESLICE_CYCLES
  env vars, so the sweep script can vary knobs without recompiling.

Sweep tooling (benches/sweep.py):
- 'run':     run the 3-file bench suite once; --save-baseline persists JSON
- 'regress': compare current run against baseline.json, exit 1 on any bench
             that regresses >10% vs stored medians
- 'sweep':   run the full SWEEP_GRID (10 points), print comparison table,
             optional --save-csv; binaries pre-built so no recompile per point

Sweep results (10-point grid, 1-CPU sandbox):
- The preemption knobs have very little effect on this single-CPU machine.
  Most benches move <5% across the entire grid.
- Longer timeslices (tc=600k, tc=1200k) reliably hurt spawn_storm_busy
  (+11-15%) and catch_unwind_panics (+10-12%) because actors hold the
  scheduler mutex longer per timeslice, stalling the storm of joinable tasks.
- Shorter timeslices (tc=150k) give a small improvement on many_timers
  (-3-4%) and a wash everywhere else.
- yield_in_hot_loop and uncontended_channel are essentially flat across all
  knobs — both are scheduling-dominated and call yield_now explicitly, so
  the RDTSC-driven preemption path is irrelevant.
- Conclusion: the knobs matter primarily under contention (multi-core).
  Re-run sweep on a multi-core machine before drawing tuning conclusions.
2026-05-25 13:04:58 +00:00

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smarm general benchmarks
available parallelism: 1 threads
ITERS=15 (+1 warmup, discarded)
CHAIN_DEPTH=1000, YIELD_TASKS=200×1000, PRIME_N=400000/64 workers, PP_ROUNDS=1000
================================================================================
chained_spawn: depth 1000
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 1000 | 8849 | 8486 | 9224
smarm 1-thread | 1000 | 8841 | 8477 | 9108
tokio current_thread | 1000 | 124 | 124 | 219
tokio multi-thread | 1000 | 187 | 184 | 283
================================================================================
yield_many: 200 tasks × 1000 yields
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 200000 | 41681 | 41278 | 43685
smarm 1-thread | 200000 | 41721 | 41218 | 42261
tokio current_thread | 200000 | 14969 | 14940 | 15051
tokio multi-thread | 200000 | 16004 | 15868 | 17569
================================================================================
fan_out_compute: primes in [2, 400000) across 64
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 33860 | 29679 | 29516 | 30105
smarm 1-thread | 33860 | 29677 | 29594 | 31365
tokio current_thread | 33860 | 28656 | 28572 | 29239
tokio multi-thread | 33860 | 34783 | 34617 | 36531
================================================================================
ping_pong_oneshot: 1000 rounds
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 1000 | 17009 | 16822 | 17418
smarm 1-thread | 1000 | 16866 | 16723 | 17315
tokio current_thread | 1000 | 880 | 871 | 1035
tokio multi-thread | 1000 | 4263 | 4178 | 4391
smarm tokio-favored benchmarks
available parallelism: 1 threads
ITERS=15 (+1 warmup, discarded)
STORM_BACKGROUND=8, STORM_SPAWN=10000, MPSC=32×10000, TIMER_ACTORS=10000 (1–10 ms), SCALING_N=400000/64
================================================================================
spawn_storm_busy: 8 bg yielders + 10000 zero-work spawns
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 10000 | 126566 | 124995 | 130402
smarm 1-thread | 10000 | 128278 | 126209 | 135156
tokio current_thread | 10000 | 2680 | 2640 | 2787
tokio multi-thread | 10000 | 7411 | 4393 | 12421
================================================================================
mpsc_contention: 32 producers × 10000 msgs → 1 consumer
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 320000 | 9073 | 8937 | 9324
smarm 1-thread | 320000 | 9120 | 9018 | 9263
tokio current_thread | 320000 | 17245 | 17180 | 17574
tokio multi-thread | 320000 | 18518 | 17685 | 19621
================================================================================
many_timers: 10000 actors sleeping 1–10 ms
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 10000 | 141855 | 135415 | 145810
smarm 1-thread | 10000 | 138265 | 135535 | 142346
tokio current_thread | 10000 | 14441 | 13453 | 14650
tokio multi-thread | 10000 | 14956 | 14529 | 15451
================================================================================
multi_thread_scaling: primes in [2, 400000) across 64 workers
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 33860 | 30033 | 29659 | 31803
tokio multi 1-thread | 33860 | 29078 | 28963 | 30231
smarm smarm-favored benchmarks
available parallelism: 1 threads
ITERS=15 (+1 warmup, discarded)
RECURSE_DEPTH=500, HOT_YIELDS=500000×2, UNCONT_MSGS=1000000, PANIC_TASKS=10000
================================================================================
deep_recursion: depth 500
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 1 | 83 | 79 | 132
smarm 1-thread | 1 | 85 | 78 | 146
tokio current_thread | 1 | 25 | 25 | 73
tokio multi-thread | 1 | 51 | 47 | 64
================================================================================
yield_in_hot_loop: 2 actors × 500000 yields (single thread)
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 1000000 | 191352 | 188830 | 196235
tokio current_thread | 1000000 | 152382 | 150674 | 187815
================================================================================
uncontended_channel: 1→1, 1000000 msgs (single thread)
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 1000000 | 27552 | 27099 | 30612
tokio current_thread | 1000000 | 53160 | 52436 | 55255
================================================================================
catch_unwind_panics: 10000 tasks, 50% panic
================================================================================
runtime | result | median µs | min µs | max µs
--------------------------------------------------------------------------------
smarm 1-thread | 10000 | 145243 | 143291 | 173727
smarm 1-thread | 10000 | 145242 | 142819 | 148457
tokio current_thread | 10000 | 266471 | 262904 | 269145
tokio multi-thread | 10000 | 274195 | 269312 | 286111
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