Technical Architecture

Deterministic processing architecture for prime-geometric decomposition and phase-coherent signal extraction

Core Architecture Components

System Overview

Input Layer

  • • Raw byte stream ingestion
  • • Prime factorization pipeline
  • • Geometric coordinate mapping
  • • Phase extraction module

Processing Core

  • • Recursive interference engine
  • • Phase cancellation arrays
  • • Coherence detection matrix
  • • Pattern persistence cache

Output Layer

  • • Coherent pattern streams
  • • Geometric distortion metrics
  • • Phase relationship graphs
  • • Identity extraction API

Prime Decomposition Engine

The heart of SEP's geometric mapping system. Every input value undergoes prime factorization to determine its coordinate position in the information manifold. 

struct PrimeCoordinate {
    std::vector prime_factors;
    std::vector exponents;
    float geometric_distortion;
    
    Vec3 to_geometric_position() const {
        Vec3 pos(0.0f);
        for (size_t i = 0; i < prime_factors.size(); ++i) {
            float angle = i * PI / prime_factors.size();
            pos.x += prime_factors[i] * cos(angle) * exponents[i];
            pos.y += prime_factors[i] * sin(angle) * exponents[i];
            pos.z += log(prime_factors[i]) * exponents[i];
        }
        return pos;
    }
    
    float calculate_distortion() const {
        float max_prime = *std::max_element(
            prime_factors.begin(), 
            prime_factors.end()
        );
        return log(max_prime) / log(2.0f);
    }
};

Phase Interference Calculator

Implements destructive interference for noise cancellation and constructive interference for pattern reinforcement through recursive phase alignment. 

class PhaseInterference {
    ComplexBuffer signal_buffer;
    PhaseMatrix phase_history;
    
public:
    void process_iteration(const ByteStream& input) {
        auto phase_vector = extract_phase(input);
        
        // Apply recursive interference
        for (size_t i = 0; i < signal_buffer.size(); ++i) {
            Complex current = signal_buffer[i];
            Complex new_phase = phase_vector[i];
            
            // Destructive interference for noise
            float coherence = calculate_coherence(current, new_phase);
            if (coherence < NOISE_THRESHOLD) {
                signal_buffer[i] *= (1.0f - coherence);
            } else {
                // Constructive for coherent patterns
                signal_buffer[i] += new_phase * coherence;
            }
        }
        
        phase_history.update(phase_vector);
    }
};

Implementation Strategies

CUDA Kernel Architecture

Parallel Prime Factorization

__global__ void prime_factorize_kernel(
    uint32_t* input_data,
    PrimeCoordinate* output_coords,
    size_t data_size
) {
    int idx = blockIdx.x * blockDim.x + threadIdx.x;
    if (idx >= data_size) return;
    
    uint32_t value = input_data[idx];
    PrimeCoordinate coord;
    
    // Parallel trial division with shared memory
    __shared__ uint32_t prime_cache[PRIME_CACHE_SIZE];
    
    // Load primes into shared memory
    if (threadIdx.x < PRIME_CACHE_SIZE) {
        prime_cache[threadIdx.x] = device_primes[threadIdx.x];
    }
    __syncthreads();
    
    // Factorize using cached primes
    for (int i = 0; i < PRIME_CACHE_SIZE && value > 1; ++i) {
        uint32_t prime = prime_cache[i];
        uint8_t exp = 0;
        
        while (value % prime == 0) {
            value /= prime;
            exp++;
        }
        
        if (exp > 0) {
            coord.add_factor(prime, exp);
        }
    }
    
    output_coords[idx] = coord;
}

Phase Coherence Detection

__global__ void phase_coherence_kernel(
    Complex* signal_buffer,
    float* coherence_map,
    size_t buffer_size,
    int iteration
) {
    int idx = blockIdx.x * blockDim.x + threadIdx.x;
    if (idx >= buffer_size) return;
    
    // Load signal into shared memory for reduction
    __shared__ Complex local_signal[BLOCK_SIZE];
    local_signal[threadIdx.x] = signal_buffer[idx];
    __syncthreads();
    
    // Calculate local phase coherence
    float coherence = 0.0f;
    int window = min(COHERENCE_WINDOW, buffer_size - idx);
    
    for (int i = 1; i <= window; ++i) {
        if (idx + i < buffer_size) {
            Complex a = local_signal[threadIdx.x];
            Complex b = signal_buffer[idx + i];
            
            // Phase difference
            float phase_diff = arg(b) - arg(a);
            float magnitude_ratio = abs(b) / (abs(a) + EPSILON);
            
            // Coherence metric
            coherence += cos(phase_diff) * 
                        exp(-abs(magnitude_ratio - 1.0f));
        }
    }
    
    coherence_map[idx] = coherence / window;
}

Memory Management

  • • Zero-copy streaming with pinned memory buffers
  • • Circular buffer architecture for continuous processing
  • • Unified memory for CPU-GPU coherence
  • • Custom allocators for prime factor caching

Optimization Techniques

  • • Warp-level primitives for reduction operations
  • • Texture memory for prime lookup tables
  • • Dynamic parallelism for recursive decomposition
  • • Persistent kernels for stream processing

Error Handling

  • • Deterministic error propagation
  • • Checkpointing for long-running computations
  • • Automatic recovery from GPU errors
  • • Validation checksums for coherence verification

Performance Characteristics

Benchmarking Results

Throughput Metrics

Data Type CPU (MB/s) GPU (MB/s) Speedup
Financial Tick Data 12.3 287.4 23.4x
Genomic Sequences 8.7 195.2 22.4x
Network Packets 15.1 342.8 22.7x
Random Noise 18.9 412.3 21.8x

Latency Profile

Prime Factorization 0.3ms
Phase Extraction 0.2ms
Interference Processing 0.4ms
Pattern Extraction 0.1ms

Total pipeline latency: ~1.0ms per MB

Deployment Configuration

# SEP Engine Configuration
engine:
  version: 2.0.0
  mode: production
  
compute:
  device: cuda
  gpu_count: 4
  memory_pool_size: 16GB
  stream_count: 8
  
processing:
  batch_size: 1048576  # 1MB batches
  prime_cache_size: 10000
  coherence_window: 256
  interference_iterations: 7
  
  factorization:
    algorithm: parallel_trial_division
    max_prime: 1000000
    use_texture_memory: true
    
  phase_detection:
    fft_size: 8192
    overlap_ratio: 0.5
    window_function: blackman_harris
    
  pattern_extraction:
    min_coherence: 0.75
    persistence_threshold: 3
    geometric_tolerance: 0.001
    
output:
  format: msgpack
  compression: zstd
  streaming: true
  checkpoint_interval: 60s