ruvector/docs/gnn/GRAPH_VALIDATION_CHECKLIST.md
rUv 4d5d3bb092 feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40)
* docs: Add comprehensive GNN v2 implementation plans

Add 22 detailed planning documents for 19 advanced GNN features:

Tier 1 (Immediate - 3-6 months):
- GNN-Guided HNSW Routing (+25% QPS)
- Incremental Graph Learning/ATLAS (10-100x faster updates)
- Neuro-Symbolic Query Execution (hybrid neural + logical)

Tier 2 (Medium-Term - 6-12 months):
- Hyperbolic Embeddings (Poincaré ball model)
- Degree-Aware Adaptive Precision (2-4x memory reduction)
- Continuous-Time Dynamic GNN (concept drift detection)

Tier 3 (Research - 12+ months):
- Graph Condensation (10-100x smaller graphs)
- Native Sparse Attention (8-15x GPU speedup)
- Quantum-Inspired Attention (long-range dependencies)

Novel Innovations (10 experimental features):
- Gravitational Embedding Fields, Causal Attention Networks
- Topology-Aware Gradient Routing, Embedding Crystallization
- Semantic Holography, Entangled Subspace Attention
- Predictive Prefetch Attention, Morphological Attention
- Adversarial Robustness Layer, Consensus Attention

Includes comprehensive regression prevention strategy with:
- Feature flag system for safe rollout
- Performance baseline (186 tests + 6 search_v2 tests)
- Automated rollback mechanisms

Related to #38

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(micro-hnsw-wasm): Add neuromorphic HNSW v2.3 with SNN integration

## New Crate: micro-hnsw-wasm v2.3.0
- Published to crates.io: https://crates.io/crates/micro-hnsw-wasm
- 11.8KB WASM binary with 58 exported functions
- Neuromorphic vector search combining HNSW + Spiking Neural Networks

### Core Features
- HNSW graph-based approximate nearest neighbor search
- Multi-distance metrics: L2, Cosine, Dot product
- GNN extensions: typed nodes, edge weights, neighbor aggregation
- Multi-core sharding: 256 cores × 32 vectors = 8K total

### Spiking Neural Network (SNN)
- LIF (Leaky Integrate-and-Fire) neurons with membrane dynamics
- STDP (Spike-Timing Dependent Plasticity) learning
- Spike propagation through graph topology
- HNSW→SNN bridge for similarity-driven neural activation

### Novel Neuromorphic Features (v2.3)
- Spike-Timing Vector Encoding (rate-to-time conversion)
- Homeostatic Plasticity (self-stabilizing thresholds)
- Oscillatory Resonance (40Hz gamma synchronization)
- Winner-Take-All Circuits (competitive selection)
- Dendritic Computation (nonlinear branch integration)
- Temporal Pattern Recognition (spike history matching)
- Combined Neuromorphic Search pipeline

### Performance Optimizations
- 5.5x faster SNN tick (2,726ns → 499ns)
- 18% faster STDP learning
- Pre-computed reciprocal constants
- Division elimination in hot paths

### Documentation & Organization
- Reorganized docs into subdirectories (gnn/, implementation/, publishing/, status/)
- Added comprehensive README with badges, SEO, citations
- Added benchmark.js and test_wasm.js test suites
- Added DEEP_REVIEW.md with performance analysis
- Added Verilog RTL for ASIC synthesis

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
2025-12-01 22:30:15 -05:00

7.9 KiB

RuVector Graph Package - Validation Checklist

🎯 Integration Validation Status

1. Package Structure

  • ruvector-graph core library exists
  • ruvector-graph-node NAPI-RS bindings exist
  • ruvector-graph-wasm WebAssembly bindings exist
  • All packages in Cargo.toml workspace
  • All packages in package.json workspaces

2. Build System

  • Cargo workspace configuration
  • NPM scripts for graph builds
  • NAPI-RS build scripts
  • WASM build scripts
  • Feature flags configured

3. Test Coverage 🔄

  • Integration test file created (tests/graph_full_integration.rs)
  • Unit tests implemented (TODO: requires graph API)
  • Integration tests implemented (TODO: requires graph API)
  • Benchmark tests implemented (TODO: requires graph API)
  • Neo4j compatibility tests (TODO: requires graph API)

4. Examples 🔄

  • Basic graph operations example (examples/graph/basic_graph.rs)
  • Cypher queries example (examples/graph/cypher_queries.rs)
  • Hybrid search example (examples/graph/hybrid_search.rs)
  • Distributed cluster example (examples/graph/distributed_cluster.rs)
  • Examples runnable (TODO: requires graph API implementation)

5. Documentation

  • Validation checklist created
  • Example templates documented
  • Build instructions in package.json
  • API documentation (TODO: generate with cargo doc)

🔧 Build Verification

Rust Builds

# Core library
cargo build -p ruvector-graph

# With all features
cargo build -p ruvector-graph --all-features

# Distributed features
cargo build -p ruvector-graph --features distributed

# Full workspace
cargo build --workspace

NAPI-RS Build (Node.js)

npm run build:graph-node
# Or directly:
cd crates/ruvector-graph-node && napi build --platform --release

WASM Build

npm run build:graph-wasm
# Or directly:
cd crates/ruvector-graph-wasm && bash build.sh

Test Execution

# All tests
cargo test --workspace

# Graph-specific tests
cargo test -p ruvector-graph

# Integration tests
cargo test --test graph_full_integration

📊 Neo4j Compatibility Matrix

Core Features

Feature Neo4j RuVector Graph Status
Property Graph Model 🔄 In Progress
Nodes with Labels 🔄 In Progress
Relationships with Types 🔄 In Progress
Properties on Nodes/Edges 🔄 In Progress
Multi-label Support 🔄 In Progress
Transactions (ACID) 🔄 In Progress

Cypher Query Language

Query Type Neo4j RuVector Graph Status
CREATE 🔄 In Progress
MATCH 🔄 In Progress
WHERE 🔄 In Progress
RETURN 🔄 In Progress
SET 🔄 In Progress
DELETE 🔄 In Progress
MERGE 🔄 In Progress
WITH 🔄 Planned
UNION 🔄 Planned
OPTIONAL MATCH 🔄 Planned

Advanced Features

Feature Neo4j RuVector Graph Status
Path Queries 🔄 Planned
Shortest Path 🔄 Planned
Graph Algorithms 🔄 Planned
Full-text Search 🔄 Planned
Spatial Queries 🔄 Planned
Temporal Graphs 🔄 Planned

Protocol Support

Protocol Neo4j RuVector Graph Status
Bolt Protocol 🔄 Planned
HTTP API Via ruvector-server
WebSocket 🔄 Planned

Indexing

Index Type Neo4j RuVector Graph Status
B-Tree Index 🔄 In Progress
Full-text Index 🔄 Planned
Composite Index 🔄 Planned
Vector Index RuVector Extension

🚀 Performance Benchmarks

Target Performance Metrics

Operation Target Current Status
Node Insertion >100k nodes/sec TBD 🔄
Relationship Creation >50k edges/sec TBD 🔄
Simple Traversal (depth-3) <1ms TBD 🔄
Vector Search (1M vectors) <10ms TBD 🔄
Complex Cypher Query <100ms TBD 🔄
Concurrent Reads 10k+ QPS TBD 🔄
Concurrent Writes 5k+ TPS TBD 🔄

Benchmark Commands

# Run all benchmarks
cargo bench -p ruvector-graph

# Specific benchmark
cargo bench -p ruvector-graph --bench graph_operations

# With profiling
cargo bench -p ruvector-graph --features metrics

API Completeness

Core API

  • Graph Database initialization
  • Node CRUD operations
  • Relationship CRUD operations
  • Property management
  • Label/Type indexing
  • Transaction support

Query API

  • Cypher parser
  • Query planner
  • Query executor
  • Result serialization
  • Parameter binding
  • Prepared statements

Vector Integration

  • Vector embeddings on nodes
  • Vector similarity search
  • Hybrid vector-graph queries
  • Combined scoring algorithms
  • Graph-constrained vector search

Distributed API (with distributed feature)

  • Cluster initialization
  • Data sharding
  • RAFT consensus
  • Replication
  • Failover handling
  • Cross-shard queries

Bindings API

  • Node.js bindings (NAPI-RS)
  • WebAssembly bindings
  • FFI bindings (future)
  • REST API (via ruvector-server)

🔍 Quality Assurance

Code Quality

# Linting
cargo clippy --workspace -- -D warnings

# Formatting
cargo fmt --all --check

# Type checking
cargo check --workspace --all-features

Security Audit

# Dependency audit
cargo audit

# Security vulnerabilities
cargo deny check advisories

Performance Profiling

# CPU profiling
cargo flamegraph --bin ruvector-cli

# Memory profiling
valgrind --tool=memcheck target/release/ruvector-cli

📋 Pre-Release Checklist

Must Have

  • All packages compile without errors
  • Workspace structure is correct
  • Build scripts are functional
  • Integration test framework exists
  • Example templates created

Should Have 🔄

  • Core graph API implemented
  • Basic Cypher queries working
  • Node.js bindings tested
  • WASM bindings tested
  • Performance benchmarks run

Nice to Have 🎯

  • Full Cypher compatibility
  • Distributed features tested
  • Production deployment guide
  • Migration tools from Neo4j
  • Comprehensive benchmarks

🚦 Status Legend

  • Complete
  • 🔄 In Progress
  • 🎯 Planned
  • Not Supported

📝 Notes

Current Status (2024-11-25)

The RuVector Graph package structure is complete with:

  • All three packages created and integrated
  • Build system configured
  • Test framework established
  • Example templates documented

Next Steps:

  1. Implement core graph API in ruvector-graph
  2. Expose APIs through Node.js and WASM bindings
  3. Implement Cypher query parser
  4. Add vector-graph integration
  5. Run comprehensive tests and benchmarks

Known Issues

  • Graph API not yet exposed (implementation in progress)
  • Examples are templates (require API implementation)
  • Integration tests are placeholders (require API implementation)
  • Benchmarks not yet runnable (require API implementation)

Performance Goals

Based on RuVector's vector performance and Neo4j's graph performance:

  • Target: 100k+ node insertions/sec
  • Target: 50k+ relationship creations/sec
  • Target: Sub-millisecond simple traversals
  • Target: <10ms vector searches at 1M+ scale
  • Target: 10k+ concurrent read queries/sec

Compatibility Goals

  • 90%+ Cypher query compatibility with Neo4j
  • Property graph model compliance
  • Transaction ACID guarantees
  • Extensible with vector embeddings (RuVector advantage)