# UHG Library Additions Tracker

## Overview
This document tracks functionality that is currently being prototyped in the authorization hierarchy implementation that should be moved to the UHG library once validated.

## Performance Components
- [x] `uhg.performance.BatchProcessor`
  - Efficient batch processing for UHG operations
  - Memory-optimized tensor operations
  - GPU acceleration support
  - Parallel processing capabilities
  - **Implemented Features:**
    - [x] Dynamic batch sizing
    - [x] Basic GPU support
    - [x] Memory usage tracking
    - [x] Performance metrics
    - [x] Mixed precision support
    - [x] Memory pinning
    - [x] Device-specific optimizations
    - [x] Batch synchronization
    - [x] Automatic device selection
    - [x] Memory layout optimization
    - [x] Performance monitoring
    - [ ] CUDA kernel optimization
    - [ ] Multi-GPU support
    - [ ] Distributed processing
    - [ ] Load balancing

- [x] `uhg.performance.TensorOptimizer`
  - Optimized tensor operations for UHG
  - Memory-efficient implementations
  - Hardware-specific optimizations
  - Performance profiling
  - **Implemented Features:**
    - [x] Mixed precision support
    - [x] Memory layout optimization
    - [x] Basic performance tracking
    - [x] Dynamic dtype selection
    - [x] Memory pinning
    - [x] Device-specific handling
    - [x] Efficient tensor allocation
    - [x] Performance monitoring
    - [x] Automatic mixed precision
    - [x] Memory usage tracking
    - [x] Batch timing metrics
    - [ ] Custom CUDA kernels
    - [ ] Operation fusion
    - [ ] Lazy evaluation
    - [ ] Tensor core utilization

## Temporal Analysis Components
- [ ] `uhg.temporal.TimeSeriesAnalysis`
  - Time-series data representation in hyperbolic space
  - Pattern detection over time sequences
  - Temporal distance metrics
  - Change point detection

- [ ] `uhg.temporal.TemporalPatternDetector`
  - Pattern evolution tracking
  - Gradual change detection
  - Persistence monitoring
  - Temporal correlation analysis

## Pattern Analysis Components
- [x] `uhg.patterns.HyperbolicPatternDetector`
  - Pattern matching in hyperbolic space
  - Anomaly detection using UHG metrics
  - Pattern similarity scoring
  - Cross-ratio based pattern comparison
  - **Implemented Features:**
    - [x] Multi-head attention for pattern detection
    - [x] Sequence pattern analysis
    - [x] Hierarchical pattern recognition
    - [x] Pattern clustering in hyperbolic space
    - [x] Access sequence analysis
    - [x] Permission pattern detection
    - [x] Temporal pattern analysis
    - [x] Relationship pattern detection
    - [x] Pattern strength scoring
    - [x] Pattern evolution tracking
    - [x] Cross-pattern correlation
    - [x] Batch processing support
    - [x] GPU acceleration
    - [x] Mixed precision support

- [x] `uhg.patterns.CorrelationAnalyzer`
  - Complex pattern correlation
  - Multi-dimensional analysis
  - Temporal evolution tracking
  - Risk assessment
  - **Implemented Features:**
    - [x] Multi-head attention correlation
    - [x] Pattern evolution analysis
    - [x] Risk scoring
    - [x] Temporal span analysis
    - [x] Pattern strength assessment
    - [x] Cross-type correlation
    - [x] Batch processing
    - [x] Performance optimization

## Attention Components
- [x] `uhg.attention.HyperbolicAttention`
  - Multi-head attention in hyperbolic space
  - Attention-based pattern detection
  - Relationship strength weighting
  - Context-aware pattern analysis
  - **Implemented Features:**
    - Hierarchical attention mechanisms
    - Cross-level attention patterns
    - Temporal attention weighting
    - Permission-aware attention
    - Batch processing support
    - Attention score normalization
    - Cross-ratio preservation
    - Projective transformations

- [x] `uhg.attention.PatternAttention`
  - Pattern-specific attention mechanisms
  - Sequence attention for access patterns
  - Multi-scale pattern attention
  - Contextual pattern weighting
  - **Implemented Features:**
    - Access pattern attention
    - Permission pattern attention
    - Temporal pattern attention
    - Violation pattern attention
    - Pattern strength weighting
    - Attention-based clustering
    - Pattern correlation analysis
    - Anomaly detection

## Next Steps
1. Advanced GPU Optimization
   - [ ] Custom CUDA kernels for pattern operations
   - [ ] Multi-GPU pattern analysis
   - [ ] Tensor core utilization for correlation
   - [ ] Operation fusion for pattern detection

2. Pattern Analysis Enhancement
   - [ ] Advanced pattern evolution tracking
   - [ ] Cross-domain pattern correlation
   - [ ] Real-time pattern analysis
   - [ ] Pattern prediction capabilities

3. Performance Optimization
   - [ ] Distributed pattern analysis
   - [ ] Memory-efficient correlation
   - [ ] Sparse pattern representation
   - [ ] Dynamic batch optimization

## Status Tracking
| Component | Status | Priority | Dependencies |
|-----------|--------|----------|--------------|
| PatternCorrelator | Completed | High | ProjectiveUHG |
| EvolutionAnalyzer | Completed | High | PatternCorrelator |
| CUDAKernels | Not Started | High | TensorOptimizer |
| MultiGPUSupport | Not Started | High | CUDAKernels |
| AdvancedPatterns | In Progress | High | PatternCorrelator |
| PerformanceOpt | In Progress | High | Multiple |

## Notes
- All optimizations preserve UHG principles
- Cross-ratio preservation is maintained
- No tangent space operations
- Focus on numerical stability
- Performance optimization is critical
- GPU acceleration ready for testing

## Updates
[2024-03-19] - Initial document creation tracking needed UHG library components
[2024-03-19] - Added performance optimization components
[2024-03-19] - Completed basic GPU acceleration support
[2024-03-19] - Added pattern detection components
[2024-03-19] - Updated status of completed components
[2024-03-19] - Added pattern correlation components
[2024-03-19] - Completed pattern evolution tracking
[2024-03-19] - Updated status of pattern analysis features
[2024-03-19] - Added new performance optimization tasks