Documentation

🔗 Graph Theory
DAG implementation & validation
🏗️ Node Architecture
Actor model & computation units
⚡ Solana Integration
PDA management & CPI framework
🤖 AI Inference
Transformer attention mechanisms
🔐 Security Model
Cryptographic primitives
🏃 Execution Model
BPF virtual machine & runtime

Graph Theory

computational-graph.md

Directed Acyclic Graph (DAG) Implementation

The workspace implements a strict DAG topology where nodes represent computational units and edges represent data dependencies. The system enforces acyclicity through real-time topological sorting using Kahn's algorithm with a time complexity of O(V + E).

Algorithm: Topological Sort with Cycle Detection
1. Maintain in-degree count for each vertex
2. Initialize queue with zero in-degree vertices
3. Process vertices in topological order
4. Detect cycles via remaining vertex count

Connection Validation Matrix

Type compatibility is enforced through a constraint satisfaction problem (CSP) where each node connection point has a finite domain of compatible types. The system uses arc consistency algorithms to prune invalid connections.

Input Types
• Data: Structured information flow
• Control: Execution dependency
• Configuration: Parameter binding
• Event: Asynchronous trigger
Output Types
• Result: Computed output
• Signal: State change notification
• Error: Exception propagation
• Stream: Continuous data flow

Overview

Content Summary
6 Technical sections
15+ Code examples
10+ Implementation details
Complexity: Advanced