rUv
161f890ddb
fix: apply cargo fmt across workspace and fix CI issues
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- Run cargo fmt --all to fix formatting in 362 files across the entire workspace
- Add PGDG repository for PostgreSQL 17 in CI test-all-features and benchmark jobs
- Add missing rvf dependency crates to standalone Dockerfile for domain-expansion
- Add sona-learning and domain-expansion features to standalone Dockerfile build
- Create npu.rs stub for ruvector-sparse-inference (fixes rustfmt resolution error)
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-02-21 20:56:38 +00:00
Claude
bdf7059088
feat: Add benchmarks for new features + persistence integration tests
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Benchmarks (store.rs, 8 new bench tests):
- Batch scoring 10k blocks vs individual scoring
- 5-bit and 7-bit dequant fast paths (4096 values)
- 5-bit quantize fast path (4096 values)
- SVD adaptive rank selection (64x64 matrix)
- format_report and format_json throughput
- MetricsSeries trend computation (100 snapshots)
Persistence tests (10 tests, feature-gated):
- FileBlockIO: write/read, multi-tier, delete, overwrite, missing key
- FileMetaLog: append/get, upsert, iter, missing key, multi-block
354 tests pass (with --features persistence).
https://claude.ai/code/session_01Ksy165BL5nGpVoWaAfTE7t
2026-02-08 04:56:40 +00:00
Claude
f0cac3bef2
feat: Implement all 11 temporal tensor improvements
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- 5-bit quantize fast path (8 values → 5 bytes, no bit accumulator)
- 5-bit + 7-bit dequant fast paths (8-at-a-time byte extraction)
- Batch scoring: compute_scores_batch, choose_tiers_batch,
score_and_partition, top_k_coldest with partial sort
- SVD improvements: reconstruction_error, energy_captured,
compression_ratio, from_data_adaptive (auto-rank selection)
- Metrics dashboard: format_report, format_json, health_check
with StoreHealthStatus, MetricsSeries with trend analysis
- Core trait integration (TensorStore, TensorStoreExt, TensorStoreSnapshot)
- AgentDB adapter (PatternIndex, InMemoryPatternIndex, AdaptiveTiering)
- Coherence gate (CoherenceCheck, EpochTracker, verify_put)
- Persistence layer (FileBlockIO, FileMetaLog, feature-gated)
- Stress/fuzz tests (8 adversarial scenarios)
- WASM FFI end-to-end test (feature-gated behind ffi)
306 tests pass (257 unit + 12 integration + 11 benchmarks +
14 property + 8 stress + 4 doctests).
https://claude.ai/code/session_01Ksy165BL5nGpVoWaAfTE7t
2026-02-08 04:34:12 +00:00
Claude
01a6f91a89
perf: Optimize quantizer + store; add comprehensive tests
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- Eliminate round() call in quantize hot path (1.8x speedup)
- Add 3-bit dequant fast path (8-values-from-3-bytes, 2.4x speedup)
- Wire WitnessLog into TieredStore (put/get/evict audit trail)
- Add TieredStore.metrics() for aggregate store statistics
- Add TieredStore.witness_log() accessors
- Update store.get() to accept `now` tick for access tracking
- 14 property-based tests (roundtrip, bitpack, segment, delta, f16,
score monotonicity, extreme values, compression ratio, determinism)
- 11 end-to-end integration tests (lifecycle, delta chain, quality
sweep, persistence, eviction, checksum, multi-tensor, stress,
compressor-to-store, factor reconstruction, witness logging)
Benchmarks (4096-element tensors, release mode):
8-bit quantize: 10,745 ns (1.52 GB/s)
8-bit dequant: 992 ns (16.52 GB/s)
3-bit dequant: 2,998 ns (5.46 GB/s)
Zipf P95 read: 41 ns
Tier flip rate: 0.074/block/min (threshold: 0.1)
All 204 tests pass.
https://claude.ai/code/session_01Ksy165BL5nGpVoWaAfTE7t
2026-02-08 03:57:57 +00:00
Claude
7f01c3e2e4
feat: Implement temporal tensor store with block-based tiered compression
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Implements the block-based storage engine specified in ADR-018 through
ADR-023 with 5 new modules and 1 benchmark/test suite.
New modules:
- store.rs (1056 lines): BlockKey, BlockMeta, Tier, TieredStore with
HashMap index, per-tier data storage, CRC32 checksums, eviction,
and BlockIO/MetaLog/Clock traits
- tiering.rs (846 lines): EMA + popcount + recency scoring with LUT-based
fast_exp_neg, hysteresis, min_residency, budgeted maintenance,
MigrationCandidate selection, warm aggressive mode (7->5 bit)
- delta.rs (825 lines): Sparse delta format (u16 index + i16 value),
DeltaChain with bounded length and compaction, FactorSet for
low-rank reconstruction, encode/decode serialization
- metrics.rs (770 lines): WitnessLog (ring buffer), WitnessEvent enum
(Access, TierChange, Eviction, Maintenance, Compaction, etc.),
StoreMetrics aggregates, StoreSnapshot serialization
- store_ffi.rs (680 lines): tts_init/put/get/tick/stats/touch/evict
WASM exports with u128 split into hi/lo u64, feature-gated
Optimizations:
- 8-bit fast path in quantizer: direct byte read/write, no bit
accumulator. Dequant: 7313ns -> 1290ns (5.7x faster, 12.7 GB/s)
- 8-bit fast path in bitpack: direct copy, no accumulator.
Pack: 8484ns -> 742ns (11.4x), Unpack: 8845ns -> 396ns (22.3x)
- #[inline] on hot functions
Benchmark results (release, 16KB blocks):
Quantize 8-bit: 18.9us Dequant 8-bit: 1.3us (12.7 GB/s)
Quantize 3-bit: 22.5us Dequant 3-bit: 7.2us (2.3 GB/s)
Score compute: 10ns Single frame decode: 178ns
Segment 8-bit decode: 1.5us (11.2 GB/s)
Zipf P95 read: 48ns Tier flip rate: 0.074/block/min
Quality (all PASS):
8-bit: 0.39% max error 7-bit: 0.79% max error
5-bit: 3.33% max error 3-bit: 16.67% max error
Tests: 170 unit + 12 integration/benchmark, all passing.
https://claude.ai/code/session_01Ksy165BL5nGpVoWaAfTE7t
2026-02-08 03:18:51 +00:00
