tests/cert.rs signs and then accepts its own signatures, which would hold just as well if the domain tag, the group assignment or the point encoding were all wrong in the same direction twice. These vectors come from the implementation the network runs — luxfi/ crypto/bls signing chain.CanonicalVoteMessage — so a Go public key is registered here, a Go signature verifies under it, and a certificate every one of whose signatures Go made is accepted by this predicate. That is a Rust node and a Go node accepting each other's votes rather than each other's shape. The header of the file records the program that regenerates them.
Lux Consensus Source Code Organization
This directory contains implementations of the Lux consensus framework in multiple programming languages. Each language implementation provides the same consensus algorithms with language-specific optimizations and idioms.
Directory Structure
src/
├── c/ # C implementation (high-performance, minimal overhead)
├── cpp/ # C++ implementation with MLX extensions (GPU acceleration)
├── go/ # Go implementation (production blockchain integration)
├── python/ # Python implementation (research and prototyping)
└── rust/ # Rust implementation (memory-safe systems programming)
Language Implementations
Go (/src/go/)
- Status: Production-ready
- Use Case: Core blockchain node integration
- Import Path:
github.com/luxfi/consensus(via go.work at root) - Features: Full integration with Lux node, concurrent processing
C (/src/c/)
- Status: Data structures only — not real consensus (per SDK audit)
- Use Case: Embedded systems, performance-critical applications
- Features: Minimal dependencies, ZeroMQ networking, SIMD optimizations
Rust (/src/rust/)
- Status: FFI wrapper around the C library — inherits C limitations, not native consensus (per SDK audit)
- Use Case: Memory-safe systems, async applications
- Features: Zero-cost abstractions, async/await, compile-time guarantees
Python (/src/python/)
- Status: Research/Development
- Use Case: Prototyping, research, data analysis
- Features: NumPy integration, ML frameworks, visualization
C++ (/src/cpp/)
- Status: Development
- Use Case: High-performance with GPU acceleration
- Features: MLX extensions, template metaprogramming, SIMD/GPU support
Building
From the repository root:
# Build all implementations
make build
# Build specific language
make build-go
make build-c
make build-rust
make build-python
make build-cpp
Testing
From the repository root:
# Test all implementations
make test
# Test specific language
make test-go
make test-c
make test-rust
make test-python
make test-cpp
Consensus Engines
All implementations support these consensus engines (Quasar family):
- Wave - Threshold voting with fast probabilistic consensus (production)
- Nova - Linear chain consensus (wraps Ray sub-protocol)
- Nebula - DAG consensus with safe-prefix commit (wraps Field sub-protocol)
- PostQuantum - Quantum-resistant consensus with BLS + Pulsar + ML-DSA
- Chain - Linear chain consensus for ordered blocks
- DAG - Full directed acyclic graph consensus
Performance Benchmarks
| Implementation | Votes/Second | Memory Usage | Latency |
|---|---|---|---|
| C | 14,000+ | < 10 MB | < 1ms |
| Rust | 13,500+ | < 15 MB | < 1ms |
| Go | 12,000+ | < 20 MB | < 2ms |
| C++ (w/ MLX) | 15,000+ | < 25 MB | < 1ms |
| Python | 5,000+ | < 50 MB | < 5ms |
Note. These per-implementation votes/sec figures are unverified and, per the SDK audit, several measure data-structure insertion on stub/wrapper SDKs (C = data structures only, Rust = FFI wrapper over C, C++ = Wave-only stub); only the Python SDK implements real consensus. Treat as illustrative, not measured consensus throughput. See
.github/workflows/README.mdand the "Honest Assessment" block inLLM.md.
Protocol Compatibility
All implementations use the same binary protocol for network communication:
┌─────────────┬────────────┬──────────┬───────────┬──────────┐
│ Engine Type │ Node ID │ Block ID │ Vote Type │ Reserved │
│ (1 byte) │ (2 bytes) │ (2 bytes)│ (1 byte) │ (2 bytes)│
└─────────────┴────────────┴──────────┴───────────┴──────────┘
This ensures interoperability between different language implementations.
Development Guidelines
- Consistency: All implementations should provide the same consensus guarantees
- Testing: Each implementation must have comprehensive test coverage
- Documentation: Language-specific documentation in
docs/{language}/ - Performance: Optimize for language strengths while maintaining correctness
- Compatibility: Maintain protocol compatibility across all implementations
Contributing
When adding features or fixes:
- Implement in the reference implementation (Go)
- Port to other languages maintaining consistency
- Add tests for all implementations
- Update documentation
See CONTRIBUTING.md for detailed guidelines.
License
Copyright (C) 2019-2025, Lux Industries Inc. All rights reserved.