perf(agent): cheaper novelty scoring; complete the consolidation benchmark
consolidation_efficiency never finished: stopped after 19 minutes on one core while building its 100K case. Not the consolidation cycle (linear: 17 us at 100 records, 2.16 ms at 10K) but the setup — every add_memory scores the new record's novelty against the whole working tier, the benchmark lets that tier reach 50K, and each comparison recomputed both norms: ~5e9 comparisons of three passes each. ImportanceScorer::score_surprise now computes the new record's norm once, takes each comparison in one fused, 8-lane pass (dot product and the other norm together), and splits a working tier of 4096+ records across threads with the `parallel` feature. Same results: tested against the old cosine formula, including shorter, empty and zero vectors and the parallel path. The work stays quadratic in the working-tier size by design; with regular consolidation the tier stays near working_capacity (100) and inserts are cheap. The complete run takes 8 min 10 s on tank and fills in the 100K cycle row (46.66 ms) and the memory-reduction table, which had never been published. The binary no longer prints a record-count ratio as a "BM25 Speedup" (never measured; Part 1 measures search latency) or claims sub-linear cycle scaling (its own numbers grow slightly faster than linearly). Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
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@@ -305,8 +305,8 @@ exactly; the `i8` column was not re-run.
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| Hit@1 recall (signal records) | 100% | 100% | no loss |
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| Search latency (avg) | 2.22 ms | 0.24 ms | **9.3x faster** |
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The consolidation cycle that does this took 0.13 ms; at 10K records a cycle
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takes 2.16 ms.
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The consolidation cycle that does this took 0.13 ms; a cycle over 10K records
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takes 2.81 ms and over 100K 46.7 ms.
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**Full benchmark details: [BENCHMARKS.md](BENCHMARKS.md)**
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