A revolutionary neuromorphic computing kernel implementing Deep Tree Echo State Networks (DTESN) for real-time cognitive processing.
Echo.Kern is a specialized real-time operating system kernel designed to provide native support for Deep Tree Echo State Networks (DTESN). It represents a groundbreaking synthesis of three fundamental computational architectures, unified by the OEIS A000081 rooted tree enumeration as their topological foundation.
graph TD
A[OEIS A000081<br/>Rooted Tree Foundation] --> B[Deep Aspects<br/>P-System Membranes]
A --> C[Tree Aspects<br/>B-Series Ridges]
A --> D[ESN Core<br/>Elementary Differentials]
B --> E[Echo.Kern<br/>Unified Implementation]
C --> E
D --> E
E --> F[Real-time Neuromorphic<br/>Computing Platform]
style A fill:#e1f5fe
style E fill:#f3e5f5
style F fill:#e8f5e8
- Hierarchical membrane structures for parallel computation
- P-lingua rule evolution within kernel space
- Cross-membrane communication following tree topology
- Mathematical B-series computation for differential operators
- Rooted tree enumeration for structural organization
- Ridge-based topological processing
- Reservoir computing with temporal dynamics
- ODE-based state evolution
- Real-time learning and adaptation
The kernel is built upon OEIS A000081 - the enumeration of unlabeled rooted trees:
A000081: 1, 1, 2, 4, 9, 20, 48, 115, 286, 719, 1842, 4766, 12486, ...
Asymptotic Growth: T(n) ~ D Ξ±^n n^(-3/2)
where:
D β 0.43992401257...
Ξ± β 2.95576528565...
This enumeration provides the fundamental topological grammar for all DTESN subsystems.
- Linux kernel development environment
- GCC 9.0+ with real-time extensions
- Python 3.8+ for specification tools
- Mermaid CLI for diagram generation
# Clone the repository
git clone https://github.com/EchoCog/echo.kern.git
cd echo.kern
# Review the kernel specification
python echo_kernel_spec.py
# Build documentation
make docs
# Build kernel (implementation in progress)
make kernel
# Interactive Deep Tree Echo demonstration
open index.html
# Explore P-System membrane computing
python -m plingua_guide
# Review technical specifications
make docs && open docs/index.html
- DEVELOPMENT.md - Development setup and contribution guidelines
- DTESN Architecture - Detailed technical architecture
- Kernel Specification - Complete implementation specification
- P-System Guide - P-lingua membrane computing guide
- Legacy Artifact Integration - Integration documentation for previous project artifacts
- Development Roadmap - Development milestones and roadmap
Current Phase: Architecture Definition & Specification
- Mathematical foundation (OEIS A000081)
- DTESN architecture specification
- P-System membrane computing framework
- Echo State Network core design
- Kernel implementation (in progress)
- Real-time scheduling
- Hardware abstraction layer
- Neuromorphic device drivers
See DEVO-GENESIS.md for detailed development roadmap.
The echo9/echo-kernel-functions/
directory contains organized prototype implementations and experimental code for Echo.Kern DTESN development:
dtesn-implementations/
- DTESN component implementations (P-Systems, B-Series, ESN, OEIS validation)kernel-modules/
- Real-time kernel module implementations and build systemneuromorphic-drivers/
- Hardware abstraction layer for neuromorphic devicesreal-time-extensions/
- Real-time scheduler extensions and performance validation
# Validate entire echo9 area
make echo9-validate
# Test DTESN prototypes
make echo9-test
# Build kernel modules (requires kernel headers)
make echo9-modules
All echo9 components follow DTESN coding standards and integrate with the main project validation system.
- Real-time Determinism: Bounded response times for critical operations
- Neuromorphic Optimization: Native support for event-driven computation
- Mathematical Rigor: Implementation faithful to OEIS A000081 enumeration
- Energy Efficiency: Optimized for low-power neuromorphic hardware
- Scalability: Support for hierarchical reservoir architectures
Operation | Requirement | Rationale |
---|---|---|
Membrane Evolution | β€ 10ΞΌs | P-system rule application |
B-Series Computation | β€ 100ΞΌs | Elementary differential evaluation |
ESN Update | β€ 1ms | Reservoir state propagation |
Context Switch | β€ 5ΞΌs | Real-time task switching |
We welcome contributions to Echo.Kern! Please see DEVELOPMENT.md for:
- Development environment setup
- Coding standards and guidelines
- Testing procedures
- Contribution workflow
The project uses automated issue generation systems:
General Development:
- Development tasks are defined in DEVO-GENESIS.md
- GitHub workflow automatically creates issues from roadmap
- See generate-next-steps.yml
C/C++ Kernel Implementation:
- Specialized Issue Generator: generate-cpp-kernel-issues.yml
- Feature Database: cpp-kernel-features.json
- Documentation: C++ Kernel Issue Generator Guide
- Validation Tool:
scripts/validate-cpp-kernel-config.py
The C/C++ kernel workflow generates detailed implementation issues with:
- Technical specifications and performance targets
- Code templates and structure guidelines
- Comprehensive testing requirements
- OEIS A000081 compliance checks
- Real-time constraint validation
This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.
- OEIS A000081 - Unlabeled rooted trees enumeration
- Echo State Networks - Reservoir computing fundamentals
- P-System Computing - Membrane computing theory
- Real-time Systems - Real-time operating systems
Echo.Kern - Where memory lives, connections flourish, and every computation becomes part of something greater than the sum of its parts.