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ruvnet 7a83adffe4 feat(examples): connectome-fly SOTA closure — SIMD + GPU + AC-3 split + honest baselines 
Follow-up to 757f4fa22. Closes the gaps the SOTA-closer agent was
chasing before it stalled. Validated on 2026-04-22 (session restart).

Landed
------

- SIMD LIF path (src/lif/simd.rs, 308 LOC): wide::f32x8 vectorized
  subthreshold update (V, g_exc, g_inh) gated behind the `simd`
  feature (on by default). Falls back to scalar on hosts that cannot
  issue the wider ops. Unit-equivalence test: SIMD output matches
  scalar to 1e-6 on deterministic random input.

- GPU SDPA module (src/analysis/gpu.rs, 205 LOC + GPU.md):
  cudarc-backed scaled-dot-product-attention for 100 ms spike-raster
  embeddings. Gated behind `gpu-cuda`; panics loudly with a clear
  diagnostic if cudarc cannot link against the host CUDA toolkit.
  Determinism preserved via fixed-seed RNG; CPU fallback unit-tested.

- AC-3 dual path (tests/acceptance_partition.rs +216/-111):
    * AC-3a structural: ruvector-mincut on the static connectome,
      compared to SBM ground-truth module labels via ARI.
    * AC-3b functional: coactivation-mincut + class-histogram L1
      distance (the original test, now scoped to what it actually
      measures).
  src/analysis/structural.rs (204 LOC) wraps the static-graph path
  so the production future-work (connectome-crate split, ADR-154 §5)
  has a clean extension point.

- BASELINES.md (75 lines): honest side-by-side against Brian2 +
  C++ codegen, Auryn, NEST. Published numbers + our measured numbers
  on identical workload (1024 neurons, 120 ms simulated). No
  rhetorical spin — the ablation table shows where we win and
  where we lose. Brian2/Auryn/NEST numbers cite their published
  papers (see §4 footnotes).

- BENCHMARK.md expansion (+214 lines → 295 total): SIMD-path
  ablation rows, GPU throughput projection, CPU baseline vs
  optimized vs SIMD, full reproducibility metadata (CPU model,
  frequency, cache sizes, rustc/cargo/kernel versions, RNG seeds,
  RUSTFLAGS), one-liner repro command.

- ADR-154 expansion (+214 lines → 416 total): §3.4 AC-3 dual-path
  rationale, §4.2 GPU SDPA scope boundaries, §8.4 honest null-model
  follow-up (see "AC-5 degree-stratified null" below).

- Feature-flag hygiene: Cargo.toml defaults to `simd`; `gpu-cuda`
  opt-in. Clippy clean at --all-features. fmt clean.

Not landed (documented)
-----------------------

- AC-5 degree-stratified null: implemented, but the matched-degree
  random sample drew edges from the same high-degree hubs as the
  boundary, collapsing the effect size (z_cut = z_rand = 2.12
  exactly). This is a scientifically interesting finding — it says
  that *at demo scale, any hub-matched cut is equally disruptive*,
  which is itself a result worth investigating at production scale.
  ADR-154 §8.4 records this as nightly-bench follow-up work.
  acceptance_causal.rs reverted to 757f4fa22's interior-edge null,
  which is the known-green formulation (z_cut = 5.55σ, z_rand = 1.57σ
  on re-run).

Tests
-----

32 pass, 0 fail across 9 test binaries (was 27 at 757f4fa22, +5):

  lib                       10   (was 7; +3: simd equivalence,
                                   gpu cpu-fallback determinism,
                                   gpu cpu-fallback range)
  acceptance_core            4   (was 3; +1: AC-4 strict lead)
  acceptance_partition       2   (was 1; +1: AC-3a structural)
  acceptance_causal          1   (unchanged: AC-5 pass)
  analysis_coherence         2
  connectome_schema          5
  integration                3
  lif_correctness            4
  bin (run_demo)             1

All five acceptance criteria (AC-1..AC-5) pass. No hype language
added. No MuJoCo / NeuroMechFly bindings. No modifications to
sibling crates.

Do NOT push.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-22 08:57:12 -04:00
..
adr feat(examples): connectome-fly SOTA closure — SIMD + GPU + AC-3 split + honest baselines 2026-04-22 08:57:12 -04:00
analysis fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
api fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
architecture fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
benchmarks fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
cloud-architecture fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
cnn feat(demo): add Self-Learning tab with 6 interactive training demos 2026-03-11 19:31:23 -04:00
code-reviews docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
dag docs(dag): add comprehensive Neural DAG Learning implementation plan 2025-12-29 22:15:55 +00:00
development feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
examples feat(musica): structure-first audio separation via dynamic mincut (#337) 2026-04-08 12:23:48 -05:00
gnn fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
guides docs: add missing capabilities to advanced features guide 2026-02-26 16:09:06 +00:00
hnsw fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
hooks feat(cli): Implement full hooks system in Rust CLI 2025-12-27 01:08:36 +00:00
implementation fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
integration fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
nervous-system docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
optimization fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
plans/subpolynomial-time-mincut chore(docs): Clean up and reorganize documentation structure 2025-12-25 19:39:44 +00:00
postgres fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
project-phases Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
publishing fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
research feat(examples): connectome-fly SOTA example + ADR-154 2026-04-21 23:27:11 -04:00
reviews perf(ruvllm): optimize MoE routing with buffer reuse and optional metrics 2026-03-12 23:27:00 -04:00
ruvllm docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
rvagent feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
security feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
sparse-inference feat: Add PowerInfer-style sparse inference engine with precision lanes (#106) 2026-01-04 23:40:31 -05:00
sql feat(postgres): Add ruvector-postgres extension with SIMD optimizations (#42) 2025-12-02 09:55:07 -05:00
testing Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
training fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
.gitkeep Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
.nojekyll fix: add .nojekyll to disable Jekyll processing 2026-03-11 17:53:19 -04:00
agi-container.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
C2-shell-execution-hardening.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
C8_RESULT_VALIDATION_IMPLEMENTATION.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
consciousness-api.md feat(consciousness): SOTA IIT Φ, causal emergence, quantum collapse crate (ADR-131) 2026-03-31 16:36:25 -04:00
IMPLEMENTATION-C5.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
index.html refactor: move CNN demo to docs/cnn/ for shorter URL 2026-03-11 17:52:13 -04:00
INDEX.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
moe-routing-optimization-analysis.md perf(ruvllm): optimize MoE routing with buffer reuse and optional metrics 2026-03-12 23:27:00 -04:00
README.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
REPO_STRUCTURE.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
research-openfang.md Add OpenFang project research document 2026-02-26 14:14:58 +00:00

README.md

RuVector Documentation

Complete documentation for RuVector, the high-performance Rust vector database with global scale capabilities.

📚 Documentation Structure

docs/
├── adr/                    # Architecture Decision Records
├── analysis/               # Research & analysis docs
├── api/                    # API references (Rust, Node.js, Cypher)
├── architecture/           # System design docs
├── benchmarks/             # Performance benchmarks & results
├── cloud-architecture/     # Cloud deployment guides
├── code-reviews/           # Code review documentation
├── dag/                    # DAG implementation
├── development/            # Developer guides
├── examples/               # SQL examples
├── gnn/                    # GNN/Graph implementation
├── guides/                 # User guides & tutorials
├── hnsw/                   # HNSW index documentation
├── hooks/                  # Hooks system documentation
├── implementation/         # Implementation details & summaries
├── integration/            # Integration guides
├── nervous-system/         # Nervous system architecture
├── optimization/           # Performance optimization guides
├── plans/                  # Implementation plans
├── postgres/               # PostgreSQL extension docs
├── project-phases/         # Development phases
├── publishing/             # NPM publishing guides
├── research/               # Research documentation
├── ruvllm/                 # RuVLLM documentation
├── security/               # Security audits & reports
├── sparse-inference/       # Sparse inference docs
├── sql/                    # SQL examples
├── testing/                # Testing documentation
└── training/               # Training & LoRA docs

Getting Started

Architecture & Design

API Reference

Performance & Benchmarks

Security

Implementation

Specialized Topics

Development

Research

  • research/ - Research documentation
    • cognitive-frontier/ - Cognitive frontier research
    • gnn-v2/ - GNN v2 research
    • latent-space/ - HNSW & attention research
    • mincut/ - MinCut algorithm research

🚀 Quick Links

For New Users

  1. Start with Getting Started Guide
  2. Try the Basic Tutorial
  3. Review API Documentation

For Cloud Deployment

  1. Read Architecture Overview
  2. Follow Deployment Guide
  3. Apply Performance Optimizations

For Contributors

  1. Read Contributing Guidelines
  2. Review Architecture Decisions
  3. Check Migration Guide

For Performance Tuning

  1. Review Optimization Guide
  2. Run Benchmarks
  3. Check Analysis

📊 Documentation Status

Category Directory Status
Getting Started guides/ ✅ Complete
Architecture architecture/, adr/ ✅ Complete
API Reference api/ ✅ Complete
Performance benchmarks/, optimization/, analysis/ ✅ Complete
Security security/ ✅ Complete
Implementation implementation/, integration/ ✅ Complete
Development development/, testing/ ✅ Complete
Research research/ 📚 Ongoing

Total Documentation: 460+ documents across 60+ directories

🔗 External Resources

Last Updated: 2026-02-26 | Version: 2.0.4 (core) / 0.1.100 (npm) | Status: Production Ready