scirs2_sparse/realtime_performance_monitor/

monitor.rs

//! Real-Time Performance Monitor Implementation
//!
//! This module contains the main RealTimePerformanceMonitor implementation
//! that coordinates all monitoring, alerting, and analysis components.

use super::alerts::{Alert, AlertManager};
use super::config::PerformanceMonitorConfig;
use super::history::PerformanceHistory;
use super::metrics::{PerformanceSample, ProcessorType, SystemMetrics};
use crate::adaptive_memory_compression::MemoryStats;
use crate::error::SparseResult;
use crate::neural_adaptive_sparse::NeuralProcessorStats;
use crate::quantum_inspired_sparse::QuantumProcessorStats;
use crate::quantum_neural_hybrid::QuantumNeuralHybridStats;
use std::collections::HashMap;
use std::sync::atomic::{AtomicBool, AtomicUsize, Ordering};
use std::sync::{Arc, Mutex};
use std::time::{Duration, SystemTime, UNIX_EPOCH};

/// Real-time performance monitor for Advanced processors
pub struct RealTimePerformanceMonitor {
    config: PerformanceMonitorConfig,
    monitoring_active: Arc<AtomicBool>,
    sample_counter: AtomicUsize,
    performance_history: Arc<Mutex<PerformanceHistory>>,
    system_metrics: Arc<Mutex<SystemMetrics>>,
    alert_manager: Arc<Mutex<AlertManager>>,
    processor_registry: Arc<Mutex<ProcessorRegistry>>,
}

/// Registry of monitored processors
pub struct ProcessorRegistry {
    quantum_processors: HashMap<String, Box<dyn QuantumProcessorMonitor>>,
    neural_processors: HashMap<String, Box<dyn NeuralProcessorMonitor>>,
    hybrid_processors: HashMap<String, Box<dyn HybridProcessorMonitor>>,
    memory_compressors: HashMap<String, Box<dyn MemoryCompressorMonitor>>,
}

/// Monitoring traits for different processor types
pub trait QuantumProcessorMonitor: Send + Sync {
    fn get_stats(&self) -> QuantumProcessorStats;
    fn get_id(&self) -> &str;
}

pub trait NeuralProcessorMonitor: Send + Sync {
    fn get_stats(&self) -> NeuralProcessorStats;
    fn get_id(&self) -> &str;
}

pub trait HybridProcessorMonitor: Send + Sync {
    fn get_stats(&self) -> QuantumNeuralHybridStats;
    fn get_id(&self) -> &str;
}

pub trait MemoryCompressorMonitor: Send + Sync {
    fn get_stats(&self) -> MemoryStats;
    fn get_id(&self) -> &str;
}

/// Monitoring summary information
#[derive(Debug, Clone)]
pub struct MonitoringSummary {
    pub monitoring_active: bool,
    pub total_samples: usize,
    pub active_alerts: usize,
    pub registered_processors: usize,
    pub uptime_seconds: u64,
    pub average_sampling_rate: f64,
    pub system_health_score: f64,
}

impl RealTimePerformanceMonitor {
    /// Create a new real-time performance monitor
    pub fn new(config: PerformanceMonitorConfig) -> Self {
        let performance_history = PerformanceHistory::new(config.max_samples);
        let system_metrics = SystemMetrics::new();
        let alert_manager = AlertManager::new(config.max_alert_history);
        let processor_registry = ProcessorRegistry::new();

        Self {
            config,
            monitoring_active: Arc::new(AtomicBool::new(false)),
            sample_counter: AtomicUsize::new(0),
            performance_history: Arc::new(Mutex::new(performance_history)),
            system_metrics: Arc::new(Mutex::new(system_metrics)),
            alert_manager: Arc::new(Mutex::new(alert_manager)),
            processor_registry: Arc::new(Mutex::new(processor_registry)),
        }
    }

    /// Start real-time monitoring
    pub fn start_monitoring(&self) -> SparseResult<()> {
        if self.monitoring_active.swap(true, Ordering::Relaxed) {
            return Ok(()); // Already running
        }

        let monitoring_active = Arc::clone(&self.monitoring_active);
        let config = self.config.clone();
        let performance_history = Arc::clone(&self.performance_history);
        let system_metrics = Arc::clone(&self.system_metrics);
        let alert_manager = Arc::clone(&self.alert_manager);
        let processor_registry = Arc::clone(&self.processor_registry);
        let sample_counter = AtomicUsize::new(0);

        // Spawn monitoring thread
        std::thread::spawn(move || {
            let interval = Duration::from_millis(config.monitoring_interval_ms);

            while monitoring_active.load(Ordering::Relaxed) {
                let start_time = std::time::Instant::now();

                // Update system metrics if enabled
                if config.enable_system_metrics {
                    if let Ok(mut metrics) = system_metrics.lock() {
                        Self::update_system_metrics(&mut metrics);
                    }
                }

                // Collect processor performance samples
                if let Ok(registry) = processor_registry.lock() {
                    let samples = Self::collect_processor_samples(&registry);

                    for sample in samples {
                        sample_counter.fetch_add(1, Ordering::Relaxed);

                        // Add to history
                        if let Ok(mut history) = performance_history.lock() {
                            history.add_sample(sample.clone());
                        }

                        // Process for alerts
                        if config.enable_alerts {
                            if let Ok(mut alerts) = alert_manager.lock() {
                                alerts.process_sample(&sample, None);
                            }
                        }
                    }
                }

                // Cleanup old data periodically
                if sample_counter.load(Ordering::Relaxed).is_multiple_of(1000) {
                    if let Ok(mut history) = performance_history.lock() {
                        let retention_time = config.optimization_interval_s * 1000 * 10; // 10x optimization interval
                        history.cleanup_old_samples(retention_time);
                    }
                }

                // Maintain monitoring interval
                let elapsed = start_time.elapsed();
                if elapsed < interval {
                    std::thread::sleep(interval - elapsed);
                }
            }
        });

        Ok(())
    }

    /// Stop monitoring
    pub fn stop_monitoring(&self) {
        self.monitoring_active.store(false, Ordering::Relaxed);
    }

    /// Check if monitoring is active
    pub fn is_monitoring_active(&self) -> bool {
        self.monitoring_active.load(Ordering::Relaxed)
    }

    /// Register a quantum processor for monitoring
    pub fn register_quantum_processor<T>(&self, processor: T) -> SparseResult<()>
    where
        T: QuantumProcessorMonitor + 'static,
    {
        if let Ok(mut registry) = self.processor_registry.lock() {
            let id = processor.get_id().to_string();
            registry.quantum_processors.insert(id, Box::new(processor));
        }
        Ok(())
    }

    /// Register a neural processor for monitoring
    pub fn register_neural_processor<T>(&self, processor: T) -> SparseResult<()>
    where
        T: NeuralProcessorMonitor + 'static,
    {
        if let Ok(mut registry) = self.processor_registry.lock() {
            let id = processor.get_id().to_string();
            registry.neural_processors.insert(id, Box::new(processor));
        }
        Ok(())
    }

    /// Register a hybrid processor for monitoring
    pub fn register_hybrid_processor<T>(&self, processor: T) -> SparseResult<()>
    where
        T: HybridProcessorMonitor + 'static,
    {
        if let Ok(mut registry) = self.processor_registry.lock() {
            let id = processor.get_id().to_string();
            registry.hybrid_processors.insert(id, Box::new(processor));
        }
        Ok(())
    }

    /// Register a memory compressor for monitoring
    pub fn register_memory_compressor<T>(&self, compressor: T) -> SparseResult<()>
    where
        T: MemoryCompressorMonitor + 'static,
    {
        if let Ok(mut registry) = self.processor_registry.lock() {
            let id = compressor.get_id().to_string();
            registry.memory_compressors.insert(id, Box::new(compressor));
        }
        Ok(())
    }

    /// Get monitoring summary
    pub fn get_monitoring_summary(&self) -> MonitoringSummary {
        let monitoring_active = self.is_monitoring_active();
        let total_samples = self.sample_counter.load(Ordering::Relaxed);

        let active_alerts = if let Ok(alerts) = self.alert_manager.lock() {
            alerts.get_active_alerts().len()
        } else {
            0
        };

        let registered_processors = if let Ok(registry) = self.processor_registry.lock() {
            registry.total_processor_count()
        } else {
            0
        };

        let system_health_score = if let Ok(metrics) = self.system_metrics.lock() {
            metrics.health_score()
        } else {
            0.0
        };

        MonitoringSummary {
            monitoring_active,
            total_samples,
            active_alerts,
            registered_processors,
            uptime_seconds: 0,          // Would track actual uptime
            average_sampling_rate: 0.0, // Would calculate from interval
            system_health_score,
        }
    }

    /// Get recent performance samples
    pub fn get_recent_samples(&self, count: usize) -> Vec<PerformanceSample> {
        if let Ok(history) = self.performance_history.lock() {
            history
                .get_recent_samples(count)
                .into_iter()
                .cloned()
                .collect()
        } else {
            Vec::new()
        }
    }

    /// Get active alerts
    pub fn get_active_alerts(&self) -> Vec<Alert> {
        if let Ok(alerts) = self.alert_manager.lock() {
            alerts.get_active_alerts().into_iter().cloned().collect()
        } else {
            Vec::new()
        }
    }

    /// Get system metrics
    pub fn get_system_metrics(&self) -> Option<SystemMetrics> {
        self.system_metrics
            .lock()
            .ok()
            .map(|metrics| metrics.clone())
    }

    /// Record a custom performance sample
    pub fn record_sample(&self, sample: PerformanceSample) -> SparseResult<()> {
        self.sample_counter.fetch_add(1, Ordering::Relaxed);

        // Add to history
        if let Ok(mut history) = self.performance_history.lock() {
            history.add_sample(sample.clone());
        }

        // Process for alerts
        if self.config.enable_alerts {
            if let Ok(mut alerts) = self.alert_manager.lock() {
                alerts.process_sample(&sample, None);
            }
        }

        Ok(())
    }

    /// Get processor performance summary
    pub fn get_processor_summary(&self) -> Vec<super::history::ProcessorSummary> {
        if let Ok(history) = self.performance_history.lock() {
            history.get_processor_summary()
        } else {
            Vec::new()
        }
    }

    /// Clear all monitoring data
    pub fn clear_data(&self) -> SparseResult<()> {
        if let Ok(mut history) = self.performance_history.lock() {
            history.clear();
        }

        if let Ok(mut alerts) = self.alert_manager.lock() {
            alerts.clear_all_alerts();
        }

        self.sample_counter.store(0, Ordering::Relaxed);

        Ok(())
    }

    // Private helper methods

    fn collect_processor_samples(registry: &ProcessorRegistry) -> Vec<PerformanceSample> {
        let mut samples = Vec::new();

        // Collect from quantum processors
        for (id, processor) in &registry.quantum_processors {
            let stats = processor.get_stats();
            let sample = Self::quantum_stats_to_sample(id, &stats);
            samples.push(sample);
        }

        // Collect from neural processors
        for (id, processor) in &registry.neural_processors {
            let stats = processor.get_stats();
            let sample = Self::neural_stats_to_sample(id, &stats);
            samples.push(sample);
        }

        // Collect from hybrid processors
        for (id, processor) in &registry.hybrid_processors {
            let stats = processor.get_stats();
            let sample = Self::hybrid_stats_to_sample(id, &stats);
            samples.push(sample);
        }

        // Collect from memory compressors
        for (id, compressor) in &registry.memory_compressors {
            let stats = compressor.get_stats();
            let sample = Self::memory_stats_to_sample(id, &stats);
            samples.push(sample);
        }

        samples
    }

    fn quantum_stats_to_sample(id: &str, stats: &QuantumProcessorStats) -> PerformanceSample {
        PerformanceSample::new(ProcessorType::QuantumInspired, id.to_string())
            .with_execution_time(stats.evolution_time * 1000.0) // Convert to ms
            .with_throughput(stats.operations_count as f64)
            .with_cache_hit_ratio(stats.cache_efficiency)
            .with_error_rate(stats.decoherence_rate)
            .with_quantum_coherence(stats.average_logical_fidelity)
    }

    fn neural_stats_to_sample(id: &str, stats: &NeuralProcessorStats) -> PerformanceSample {
        PerformanceSample::new(ProcessorType::NeuralAdaptive, id.to_string())
            .with_throughput(stats.total_operations as f64)
            .with_cache_hit_ratio(stats.pattern_memory_hit_rate)
            .with_neural_confidence(stats.neural_network_accuracy)
            .with_custom_metric(
                "performance_improvement".to_string(),
                stats.average_performance_improvement,
            )
            .with_custom_metric("rl_reward".to_string(), stats.rl_agent_reward)
            .with_custom_metric(
                "attention_score".to_string(),
                stats.transformer_attention_score,
            )
    }

    fn hybrid_stats_to_sample(id: &str, stats: &QuantumNeuralHybridStats) -> PerformanceSample {
        PerformanceSample::new(ProcessorType::QuantumNeuralHybrid, id.to_string())
            .with_throughput(stats.total_operations as f64)
            .with_memory_usage(stats.memory_utilization * 100.0) // Convert to MB estimate
            .with_quantum_coherence(stats.quantum_coherence)
            .with_neural_confidence(stats.neural_confidence)
            .with_custom_metric("hybrid_synchronization".to_string(), stats.hybrid_synchronization)
            .with_custom_metric("entanglement_strength".to_string(), stats.entanglement_strength)
            .with_custom_metric("average_performance".to_string(), stats.average_performance)
    }

    fn memory_stats_to_sample(id: &str, stats: &MemoryStats) -> PerformanceSample {
        let compression_ratio = if stats.compression_stats.total_uncompressed_size > 0 {
            stats.compression_stats.total_compressed_size as f64
                / stats.compression_stats.total_uncompressed_size as f64
        } else {
            1.0
        };

        PerformanceSample::new(ProcessorType::MemoryCompression, id.to_string())
            .with_memory_usage(stats.current_memory_usage as f64 / (1024.0 * 1024.0))
            .with_cache_hit_ratio(stats.cache_hit_ratio)
            .with_compression_ratio(compression_ratio)
    }

    fn update_system_metrics(metrics: &mut SystemMetrics) {
        metrics.update_timestamp();

        // Simplified system metrics update
        // In a real implementation, this would query actual system stats
        metrics.cpu_usage = Self::get_cpu_usage();
        metrics.memory_usage = Self::get_memory_usage();
        metrics.gpu_usage = Self::get_gpu_usage();
        metrics.system_load = Self::get_system_load();
        metrics.temperature = Self::get_system_temperature();
    }

    // Placeholder system metrics collection methods
    fn get_cpu_usage() -> f64 {
        // Would use system APIs to get actual CPU usage
        0.0
    }

    fn get_memory_usage() -> f64 {
        // Would use system APIs to get actual memory usage
        0.0
    }

    fn get_gpu_usage() -> f64 {
        // Would use GPU APIs to get actual GPU usage
        0.0
    }

    fn get_system_load() -> f64 {
        // Would use system APIs to get actual system load
        0.0
    }

    fn get_system_temperature() -> f64 {
        // Would use hardware monitoring APIs to get temperature
        0.0
    }
}

impl ProcessorRegistry {
    fn new() -> Self {
        Self {
            quantum_processors: HashMap::new(),
            neural_processors: HashMap::new(),
            hybrid_processors: HashMap::new(),
            memory_compressors: HashMap::new(),
        }
    }

    fn total_processor_count(&self) -> usize {
        self.quantum_processors.len()
            + self.neural_processors.len()
            + self.hybrid_processors.len()
            + self.memory_compressors.len()
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    // Mock processor for testing
    struct MockQuantumProcessor {
        id: String,
    }

    impl QuantumProcessorMonitor for MockQuantumProcessor {
        fn get_stats(&self) -> QuantumProcessorStats {
            QuantumProcessorStats {
                operations_count: 100,
                coherence_time: 95.0,
                decoherence_rate: 0.1,
                entanglement_strength: 0.8,
                cache_efficiency: 0.8,
                error_correction_enabled: true,
                active_error_syndromes: 2,
                average_logical_fidelity: 0.9,
                evolution_time: 1000.0,
            }
        }

        fn get_id(&self) -> &str {
            &self.id
        }
    }

    #[test]
    fn test_monitor_creation() {
        let config = PerformanceMonitorConfig::default();
        let monitor = RealTimePerformanceMonitor::new(config);
        assert!(!monitor.is_monitoring_active());
    }

    #[test]
    fn test_processor_registration() {
        let config = PerformanceMonitorConfig::default();
        let monitor = RealTimePerformanceMonitor::new(config);

        let processor = MockQuantumProcessor {
            id: "test-quantum".to_string(),
        };

        let result = monitor.register_quantum_processor(processor);
        assert!(result.is_ok());

        let summary = monitor.get_monitoring_summary();
        assert_eq!(summary.registered_processors, 1);
    }

    #[test]
    fn test_monitoring_summary() {
        let config = PerformanceMonitorConfig::default();
        let monitor = RealTimePerformanceMonitor::new(config);

        let summary = monitor.get_monitoring_summary();
        assert!(!summary.monitoring_active);
        assert_eq!(summary.total_samples, 0);
        assert_eq!(summary.active_alerts, 0);
        assert_eq!(summary.registered_processors, 0);
    }

    #[test]
    fn test_custom_sample_recording() {
        let config = PerformanceMonitorConfig::default();
        let monitor = RealTimePerformanceMonitor::new(config);

        let sample = PerformanceSample::new(ProcessorType::QuantumInspired, "test".to_string())
            .with_execution_time(100.0);

        let result = monitor.record_sample(sample);
        assert!(result.is_ok());

        let recent_samples = monitor.get_recent_samples(10);
        assert_eq!(recent_samples.len(), 1);
    }

    #[test]
    fn test_data_clearing() {
        let config = PerformanceMonitorConfig::default();
        let monitor = RealTimePerformanceMonitor::new(config);

        // Add some data
        let sample = PerformanceSample::new(ProcessorType::QuantumInspired, "test".to_string());
        let _ = monitor.record_sample(sample);

        // Clear data
        let result = monitor.clear_data();
        assert!(result.is_ok());

        let recent_samples = monitor.get_recent_samples(10);
        assert_eq!(recent_samples.len(), 0);
    }
}