scirs2_stats/

adaptive_memory_advanced.rs

//! Advanced-advanced adaptive memory optimization system for statistical computing
//!
//! This module provides state-of-the-art memory management techniques optimized
//! for extremely large-scale statistical computations with:
//! - Dynamic memory allocation strategies
//! - Real-time memory pressure detection and response
//! - Cache-aware data structures and algorithms
//! - Memory-mapped file handling for out-of-core processing
//! - NUMA-aware memory allocation and data placement
//! - Predictive memory prefetching using machine learning
//! - Adaptive garbage collection with statistical workload awareness

use crate::error::{StatsError, StatsResult};
use scirs2_core::ndarray::{Array2, ArrayView2};
use scirs2_core::numeric::{Float, NumCast, One, Zero};
use scirs2_core::{
    parallel_ops::*,
    simd_ops::{PlatformCapabilities, SimdUnifiedOps},
};
use std::collections::{BTreeMap, HashMap, VecDeque};
use std::marker::PhantomData;
use std::sync::atomic::{AtomicU64, AtomicUsize, Ordering};
use std::sync::{Arc, Mutex, RwLock, Weak};
use std::thread;
use std::time::{Duration, Instant, SystemTime};

/// Advanced-advanced adaptive memory configuration
#[derive(Debug)]
pub struct AdaptiveMemoryConfig {
    /// Memory allocation strategies
    pub allocation_strategy: AllocationStrategy,
    /// Cache optimization settings
    pub cache_optimization: CacheOptimizationConfig,
    /// NUMA configuration
    pub numa_config: NumaConfig,
    /// Predictive settings
    pub predictive_config: PredictiveConfig,
    /// Memory pressure handling
    pub pressure_config: MemoryPressureConfig,
    /// Out-of-core processing
    pub out_of_core_config: OutOfCoreConfig,
    /// Garbage collection optimization
    pub gc_config: GarbageCollectionConfig,
}

/// Memory allocation strategy selection
#[derive(Debug, Clone, Copy)]
pub enum AllocationStrategy {
    /// Standard system allocator
    System,
    /// Custom pool allocator optimized for statistical data
    Pool,
    /// NUMA-aware allocator
    NumaAware,
    /// Memory-mapped allocator for large datasets
    MemoryMapped,
    /// Hybrid approach with automatic selection
    Adaptive,
    /// Zero-copy allocation with smart pointers
    ZeroCopy,
}

/// Cache optimization configuration
#[derive(Debug)]
pub struct CacheOptimizationConfig {
    /// Cache hierarchy information
    pub cache_hierarchy: CacheHierarchy,
    /// Cache-aware data layout strategies
    pub layout_strategy: DataLayoutStrategy,
    /// Prefetching configuration
    pub prefetch_config: PrefetchConfig,
    /// Cache line optimization
    pub cache_line_optimization: bool,
    /// Memory access pattern analysis
    pub pattern_analysis: AccessPatternConfig,
}

/// Cache hierarchy details for optimization
#[derive(Debug, Clone)]
pub struct CacheHierarchy {
    pub l1size: usize,
    pub l1_linesize: usize,
    pub l1_associativity: usize,
    pub l2size: usize,
    pub l2_linesize: usize,
    pub l2_associativity: usize,
    pub l3size: usize,
    pub l3_linesize: usize,
    pub l3_associativity: usize,
    pub tlb_entries: usize,
    pub pagesize: usize,
}

/// Data layout strategy for cache optimization
#[derive(Debug, Clone, Copy)]
pub enum DataLayoutStrategy {
    /// Row-major layout (C-style)
    RowMajor,
    /// Column-major layout (Fortran-style)
    ColumnMajor,
    /// Block-wise layout for cache efficiency
    Blocked,
    /// Z-order (Morton order) layout
    ZOrder,
    /// Hilbert curve layout
    Hilbert,
    /// Adaptive layout based on access patterns
    Adaptive,
}

/// Prefetching configuration
#[derive(Debug, Clone)]
pub struct PrefetchConfig {
    /// Enable software prefetching
    pub enable_software_prefetch: bool,
    /// Hardware prefetching hints
    pub enable_hardware_hints: bool,
    /// Prefetch distance (cache lines ahead)
    pub prefetch_distance: usize,
    /// Temporal locality awareness
    pub temporal_awareness: bool,
    /// Spatial locality awareness
    pub spatial_awareness: bool,
    /// Predictive prefetching using ML
    pub predictive_prefetch: bool,
}

/// Memory access pattern analysis
#[derive(Debug)]
pub struct AccessPatternConfig {
    /// Enable pattern detection
    pub enable_detection: bool,
    /// Pattern history size
    pub historysize: usize,
    /// Pattern prediction window
    pub prediction_window: usize,
    /// Confidence threshold for predictions
    pub confidence_threshold: f64,
    /// Update frequency for pattern analysis
    pub update_frequency: Duration,
}

/// NUMA (Non-Uniform Memory Access) configuration
#[derive(Debug)]
pub struct NumaConfig {
    /// Enable NUMA awareness
    pub enable_numa: bool,
    /// NUMA topology detection
    pub auto_detect_topology: bool,
    /// Memory binding strategy
    pub binding_strategy: NumaBindingStrategy,
    /// Thread affinity management
    pub thread_affinity: bool,
    /// Inter-node communication optimization
    pub optimize_communication: bool,
    /// Memory migration policies
    pub migration_policy: NumaMigrationPolicy,
}

/// NUMA memory binding strategy
#[derive(Debug, Clone)]
pub enum NumaBindingStrategy {
    /// Bind to local node
    Local,
    /// Interleave across all nodes
    Interleave,
    /// First-touch policy
    FirstTouch,
    /// Adaptive based on access patterns
    Adaptive,
    /// Explicit node specification
    Explicit(Vec<usize>),
}

/// NUMA memory migration policy
#[derive(Debug, Clone, Copy)]
pub enum NumaMigrationPolicy {
    /// No migration
    None,
    /// Migrate on access pattern change
    OnPatternChange,
    /// Periodic migration based on usage
    Periodic,
    /// Lazy migration when memory pressure occurs
    Lazy,
}

/// Predictive memory management configuration
#[derive(Debug)]
pub struct PredictiveConfig {
    /// Enable predictive memory management
    pub enable_prediction: bool,
    /// Machine learning model type
    pub model_type: PredictiveModelType,
    /// Training data collection
    pub collect_trainingdata: bool,
    /// Prediction accuracy target
    pub accuracy_target: f64,
    /// Model update frequency
    pub model_update_frequency: Duration,
    /// Feature extraction configuration
    pub feature_config: FeatureExtractionConfig,
}

/// Type of predictive model for memory management
#[derive(Debug, Clone, Copy)]
pub enum PredictiveModelType {
    /// Linear regression model
    LinearRegression,
    /// Polynomial regression
    PolynomialRegression,
    /// Random forest
    RandomForest,
    /// Neural network
    NeuralNetwork,
    /// LSTM for temporal patterns
    LSTM,
    /// Ensemble of multiple models
    Ensemble,
}

/// Feature extraction for predictive models
#[derive(Debug, Clone)]
pub struct FeatureExtractionConfig {
    /// Memory access frequency features
    pub access_frequency: bool,
    /// Temporal pattern features
    pub temporal_patterns: bool,
    /// Spatial locality features
    pub spatial_locality: bool,
    /// Data size and type features
    pub data_characteristics: bool,
    /// Computation type features
    pub computation_type: bool,
    /// System resource features
    pub system_resources: bool,
}

/// Memory pressure detection and response
#[derive(Debug)]
pub struct MemoryPressureConfig {
    /// Memory pressure detection thresholds
    pub pressure_thresholds: PressureThresholds,
    /// Response strategies for different pressure levels
    pub response_strategies: ResponseStrategies,
    /// Monitoring frequency
    pub monitoring_frequency: Duration,
    /// Emergency response configuration
    pub emergency_config: EmergencyResponseConfig,
}

/// Memory pressure threshold levels
#[derive(Debug, Clone)]
pub struct PressureThresholds {
    /// Low pressure threshold (% of total memory)
    pub low_threshold: f64,
    /// Medium pressure threshold
    pub medium_threshold: f64,
    /// High pressure threshold
    pub high_threshold: f64,
    /// Critical pressure threshold
    pub critical_threshold: f64,
    /// Swap usage threshold
    pub swap_threshold: f64,
}

/// Response strategies for memory pressure
#[derive(Debug, Clone)]
pub struct ResponseStrategies {
    /// Low pressure response
    pub low_pressure: Vec<PressureResponse>,
    /// Medium pressure response
    pub medium_pressure: Vec<PressureResponse>,
    /// High pressure response
    pub high_pressure: Vec<PressureResponse>,
    /// Critical pressure response
    pub critical_pressure: Vec<PressureResponse>,
}

/// Memory pressure response actions
#[derive(Debug, Clone, Copy)]
pub enum PressureResponse {
    /// Trigger garbage collection
    TriggerGC,
    /// Compress in-memory data
    CompressData,
    /// Move data to disk
    MoveToDisk,
    /// Reduce cache sizes
    ReduceCache,
    /// Simplify algorithms
    SimplifyAlgorithms,
    /// Pause non-critical operations
    PauseOperations,
    /// Request more memory
    RequestMemory,
    /// Emergency data evacuation
    EmergencyEvacuation,
}

/// Emergency response configuration
#[derive(Debug)]
pub struct EmergencyResponseConfig {
    /// Enable emergency responses
    pub enable_emergency: bool,
    /// Emergency evacuation threshold
    pub evacuation_threshold: f64,
    /// Emergency compression ratio
    pub compression_ratio: f64,
    /// Emergency disk spillover
    pub enable_spillover: bool,
    /// Recovery strategy after emergency
    pub recovery_strategy: EmergencyRecoveryStrategy,
}

/// Emergency recovery strategies
#[derive(Debug, Clone, Copy)]
pub enum EmergencyRecoveryStrategy {
    /// Gradual memory reclamation
    Gradual,
    /// Immediate full recovery
    Immediate,
    /// Conservative recovery
    Conservative,
    /// Adaptive recovery based on system state
    Adaptive,
}

/// Out-of-core processing configuration
#[derive(Debug, Clone)]
pub struct OutOfCoreConfig {
    /// Enable out-of-core processing
    pub enable_out_of_core: bool,
    /// Chunk size for out-of-core operations
    pub chunksize: usize,
    /// Number of chunks to keep in memory
    pub memory_chunks: usize,
    /// Disk storage configuration
    pub storage_config: StorageConfig,
    /// Compression for disk storage
    pub compression_config: CompressionConfig,
    /// Scheduling strategy for chunk loading
    pub scheduling_strategy: ChunkSchedulingStrategy,
}

/// Storage configuration for out-of-core processing
#[derive(Debug, Clone)]
pub struct StorageConfig {
    /// Storage type
    pub storage_type: StorageType,
    /// Storage location (directory path)
    pub storage_path: String,
    /// Temporary file naming strategy
    pub naming_strategy: NamingStrategy,
    /// File system optimization
    pub fs_optimization: FileSystemConfig,
}

/// Storage type for out-of-core data
#[derive(Debug, Clone, Copy)]
pub enum StorageType {
    /// Regular file system
    FileSystem,
    /// Memory-mapped files
    MemoryMapped,
    /// Network-attached storage
    NetworkStorage,
    /// Solid-state drive optimized
    SSDOptimized,
    /// Hard disk drive optimized
    HDDOptimized,
}

/// Temporary file naming strategy
#[derive(Debug, Clone, Copy)]
pub enum NamingStrategy {
    /// Sequential numbering
    Sequential,
    /// UUID-based names
    UUID,
    /// Hash-based names
    Hash,
    /// Timestamp-based names
    Timestamp,
}

/// File system optimization configuration
#[derive(Debug, Clone)]
pub struct FileSystemConfig {
    /// I/O scheduler hints
    pub io_scheduler: IOScheduler,
    /// Read-ahead configuration
    pub read_ahead: usize,
    /// Write-behind configuration
    pub write_behind: bool,
    /// Direct I/O for large transfers
    pub direct_io: bool,
    /// Async I/O configuration
    pub async_io: bool,
}

/// I/O scheduler type
#[derive(Debug, Clone, Copy)]
pub enum IOScheduler {
    /// No-op scheduler
    Noop,
    /// Deadline scheduler
    Deadline,
    /// Completely Fair Queuing
    CFQ,
    /// Budget Fair Queuing
    BFQ,
    /// Multi-queue
    MQ,
}

/// Compression configuration for out-of-core storage
#[derive(Debug, Clone)]
pub struct CompressionConfig {
    /// Enable compression
    pub enable_compression: bool,
    /// Compression algorithm
    pub algorithm: CompressionAlgorithm,
    /// Compression level (1-9)
    pub compression_level: u8,
    /// Compression threshold (minimum size to compress)
    pub compression_threshold: usize,
    /// Adaptive compression based on data characteristics
    pub adaptive_compression: bool,
}

/// Compression algorithms for storage
#[derive(Debug, Clone, Copy)]
pub enum CompressionAlgorithm {
    /// LZ4 - fast compression
    LZ4,
    /// Zstd - balanced compression
    Zstd,
    /// Gzip - standard compression
    Gzip,
    /// Brotli - high compression ratio
    Brotli,
    /// Snappy - Google's compression
    Snappy,
    /// Specialized floating-point compression
    FloatingPoint,
}

/// Chunk scheduling strategy for out-of-core processing
#[derive(Debug, Clone, Copy)]
pub enum ChunkSchedulingStrategy {
    /// First-in-first-out
    FIFO,
    /// Least recently used
    LRU,
    /// Least frequently used
    LFU,
    /// Predictive scheduling based on access patterns
    Predictive,
    /// Priority-based scheduling
    Priority,
    /// Adaptive scheduling
    Adaptive,
}

/// Garbage collection optimization configuration
#[derive(Debug, Clone)]
pub struct GarbageCollectionConfig {
    /// GC strategy
    pub gc_strategy: GCStrategy,
    /// GC trigger conditions
    pub trigger_conditions: GCTriggerConditions,
    /// GC performance tuning
    pub performance_tuning: GCPerformanceTuning,
    /// Statistical workload awareness
    pub workload_awareness: GCWorkloadAwareness,
}

/// Garbage collection strategy
#[derive(Debug, Clone, Copy)]
pub enum GCStrategy {
    /// No garbage collection
    None,
    /// Reference counting
    ReferenceCounting,
    /// Mark and sweep
    MarkAndSweep,
    /// Generational GC
    Generational,
    /// Incremental GC
    Incremental,
    /// Concurrent GC
    Concurrent,
    /// Statistical workload-aware GC
    StatisticalAware,
}

/// GC trigger conditions
#[derive(Debug, Clone)]
pub struct GCTriggerConditions {
    /// Memory usage threshold
    pub memory_threshold: f64,
    /// Time-based triggers
    pub timebased: Option<Duration>,
    /// Allocation count threshold
    pub allocation_threshold: usize,
    /// Memory pressure trigger
    pub pressure_trigger: bool,
    /// Predictive trigger based on patterns
    pub predictive_trigger: bool,
}

/// GC performance tuning parameters
#[derive(Debug, Clone)]
pub struct GCPerformanceTuning {
    /// Parallel GC threads
    pub parallel_threads: usize,
    /// GC pause time target
    pub pause_time_target: Duration,
    /// Incremental GC chunk size
    pub incremental_chunksize: usize,
    /// Concurrent GC enabled
    pub concurrent_enabled: bool,
    /// Background GC enabled
    pub background_enabled: bool,
}

/// Statistical workload awareness for GC
#[derive(Debug, Clone)]
pub struct GCWorkloadAwareness {
    /// Statistical operation type awareness
    pub operation_type_aware: bool,
    /// Data lifecycle analysis
    pub lifecycle_analysis: bool,
    /// Computation phase awareness
    pub phase_awareness: bool,
    /// Memory access pattern integration
    pub pattern_integration: bool,
}

impl Default for AdaptiveMemoryConfig {
    fn default() -> Self {
        Self {
            allocation_strategy: AllocationStrategy::Adaptive,
            cache_optimization: CacheOptimizationConfig::default(),
            numa_config: NumaConfig::default(),
            predictive_config: PredictiveConfig::default(),
            pressure_config: MemoryPressureConfig::default(),
            out_of_core_config: OutOfCoreConfig::default(),
            gc_config: GarbageCollectionConfig::default(),
        }
    }
}

impl Default for CacheOptimizationConfig {
    fn default() -> Self {
        Self {
            cache_hierarchy: CacheHierarchy::detect(),
            layout_strategy: DataLayoutStrategy::Adaptive,
            prefetch_config: PrefetchConfig::default(),
            cache_line_optimization: true,
            pattern_analysis: AccessPatternConfig::default(),
        }
    }
}

impl CacheHierarchy {
    fn detect() -> Self {
        // Enhanced cache detection - simplified for now
        Self {
            l1size: 32 * 1024,
            l1_linesize: 64,
            l1_associativity: 8,
            l2size: 256 * 1024,
            l2_linesize: 64,
            l2_associativity: 8,
            l3size: 8 * 1024 * 1024,
            l3_linesize: 64,
            l3_associativity: 16,
            tlb_entries: 1024,
            pagesize: 4096,
        }
    }
}

impl Default for PrefetchConfig {
    fn default() -> Self {
        Self {
            enable_software_prefetch: true,
            enable_hardware_hints: true,
            prefetch_distance: 8,
            temporal_awareness: true,
            spatial_awareness: true,
            predictive_prefetch: true,
        }
    }
}

impl Default for AccessPatternConfig {
    fn default() -> Self {
        Self {
            enable_detection: true,
            historysize: 1000,
            prediction_window: 100,
            confidence_threshold: 0.8,
            update_frequency: Duration::from_millis(100),
        }
    }
}

impl Default for NumaConfig {
    fn default() -> Self {
        Self {
            enable_numa: true,
            auto_detect_topology: true,
            binding_strategy: NumaBindingStrategy::Adaptive,
            thread_affinity: true,
            optimize_communication: true,
            migration_policy: NumaMigrationPolicy::OnPatternChange,
        }
    }
}

impl Default for PredictiveConfig {
    fn default() -> Self {
        Self {
            enable_prediction: true,
            model_type: PredictiveModelType::Ensemble,
            collect_trainingdata: true,
            accuracy_target: 0.85,
            model_update_frequency: Duration::from_secs(300),
            feature_config: FeatureExtractionConfig::default(),
        }
    }
}

impl Default for FeatureExtractionConfig {
    fn default() -> Self {
        Self {
            access_frequency: true,
            temporal_patterns: true,
            spatial_locality: true,
            data_characteristics: true,
            computation_type: true,
            system_resources: true,
        }
    }
}

impl Default for MemoryPressureConfig {
    fn default() -> Self {
        Self {
            pressure_thresholds: PressureThresholds::default(),
            response_strategies: ResponseStrategies::default(),
            monitoring_frequency: Duration::from_millis(500),
            emergency_config: EmergencyResponseConfig::default(),
        }
    }
}

impl Default for PressureThresholds {
    fn default() -> Self {
        Self {
            low_threshold: 0.7,
            medium_threshold: 0.8,
            high_threshold: 0.9,
            critical_threshold: 0.95,
            swap_threshold: 0.1,
        }
    }
}

impl Default for ResponseStrategies {
    fn default() -> Self {
        Self {
            low_pressure: vec![PressureResponse::ReduceCache],
            medium_pressure: vec![PressureResponse::TriggerGC, PressureResponse::CompressData],
            high_pressure: vec![
                PressureResponse::TriggerGC,
                PressureResponse::CompressData,
                PressureResponse::MoveToDisk,
            ],
            critical_pressure: vec![
                PressureResponse::EmergencyEvacuation,
                PressureResponse::PauseOperations,
            ],
        }
    }
}

impl Default for EmergencyResponseConfig {
    fn default() -> Self {
        Self {
            enable_emergency: true,
            evacuation_threshold: 0.98,
            compression_ratio: 0.5,
            enable_spillover: true,
            recovery_strategy: EmergencyRecoveryStrategy::Adaptive,
        }
    }
}

impl Default for OutOfCoreConfig {
    fn default() -> Self {
        Self {
            enable_out_of_core: true,
            chunksize: 64 * 1024 * 1024, // 64MB chunks
            memory_chunks: 16,
            storage_config: StorageConfig::default(),
            compression_config: CompressionConfig::default(),
            scheduling_strategy: ChunkSchedulingStrategy::Adaptive,
        }
    }
}

impl Default for StorageConfig {
    fn default() -> Self {
        Self {
            storage_type: StorageType::FileSystem,
            storage_path: "/tmp/scirs2_stats".to_string(),
            naming_strategy: NamingStrategy::UUID,
            fs_optimization: FileSystemConfig::default(),
        }
    }
}

impl Default for FileSystemConfig {
    fn default() -> Self {
        Self {
            io_scheduler: IOScheduler::MQ,
            read_ahead: 128 * 1024,
            write_behind: true,
            direct_io: false,
            async_io: true,
        }
    }
}

impl Default for CompressionConfig {
    fn default() -> Self {
        Self {
            enable_compression: true,
            algorithm: CompressionAlgorithm::Zstd,
            compression_level: 3,
            compression_threshold: 1024,
            adaptive_compression: true,
        }
    }
}

impl Default for GarbageCollectionConfig {
    fn default() -> Self {
        Self {
            gc_strategy: GCStrategy::StatisticalAware,
            trigger_conditions: GCTriggerConditions::default(),
            performance_tuning: GCPerformanceTuning::default(),
            workload_awareness: GCWorkloadAwareness::default(),
        }
    }
}

impl Default for GCTriggerConditions {
    fn default() -> Self {
        Self {
            memory_threshold: 0.8,
            timebased: Some(Duration::from_secs(60)),
            allocation_threshold: 1000000,
            pressure_trigger: true,
            predictive_trigger: true,
        }
    }
}

impl Default for GCPerformanceTuning {
    fn default() -> Self {
        Self {
            parallel_threads: num_threads().max(2),
            pause_time_target: Duration::from_millis(10),
            incremental_chunksize: 1024,
            concurrent_enabled: true,
            background_enabled: true,
        }
    }
}

impl Default for GCWorkloadAwareness {
    fn default() -> Self {
        Self {
            operation_type_aware: true,
            lifecycle_analysis: true,
            phase_awareness: true,
            pattern_integration: true,
        }
    }
}

/// Advanced-advanced adaptive memory manager
pub struct AdaptiveMemoryManager<F> {
    config: AdaptiveMemoryConfig,
    memory_pools: Arc<RwLock<HashMap<usize, Arc<MemoryPool>>>>,
    cache_manager: Arc<CacheManager>,
    numa_manager: Arc<NumaManager>,
    predictive_engine: Arc<PredictiveEngine>,
    pressure_monitor: Arc<PressureMonitor>,
    out_of_core_manager: Arc<OutOfCoreManager>,
    gc_manager: Arc<GCManager>,
    performance_monitor: Arc<MemoryPerformanceMonitor>,
    _phantom: PhantomData<F>,
}

/// Memory pool for efficient allocation
pub struct MemoryPool {
    chunksize: usize,
    available_chunks: Mutex<VecDeque<*mut u8>>,
    allocated_chunks: AtomicUsize,
    total_chunks: AtomicUsize,
    #[allow(dead_code)]
    allocation_strategy: AllocationStrategy,
    #[allow(dead_code)]
    numa_node: Option<usize>,
}

/// Cache management system
pub struct CacheManager {
    #[allow(dead_code)]
    cache_hierarchy: CacheHierarchy,
    #[allow(dead_code)]
    layout_optimizer: LayoutOptimizer,
    #[allow(dead_code)]
    prefetch_engine: PrefetchEngine,
    #[allow(dead_code)]
    access_tracker: AccessTracker,
}

/// Data layout optimizer
pub struct LayoutOptimizer {
    #[allow(dead_code)]
    current_strategy: RwLock<DataLayoutStrategy>,
    #[allow(dead_code)]
    performance_history: RwLock<VecDeque<LayoutPerformance>>,
    #[allow(dead_code)]
    adaptive_threshold: f64,
}

/// Layout performance metrics
#[derive(Debug)]
pub struct LayoutPerformance {
    strategy: DataLayoutStrategy,
    cache_hit_rate: f64,
    memory_bandwidth: f64,
    computation_time: Duration,
    timestamp: Instant,
}

/// Prefetch engine for predictive loading
pub struct PrefetchEngine {
    #[allow(dead_code)]
    prefetch_config: PrefetchConfig,
    #[allow(dead_code)]
    pattern_predictor: PatternPredictor,
    #[allow(dead_code)]
    hardware_prefetcher: HardwarePrefetcher,
}

/// Memory access pattern predictor
pub struct PatternPredictor {
    #[allow(dead_code)]
    access_history: RwLock<VecDeque<MemoryAccess>>,
    #[allow(dead_code)]
    pattern_models: RwLock<HashMap<AccessPatternType, PredictionModel>>,
    #[allow(dead_code)]
    confidence_tracker: ConfidenceTracker,
}

/// Memory access record
#[derive(Debug)]
pub struct MemoryAccess {
    address: usize,
    size: usize,
    access_type: AccessType,
    timestamp: Instant,
    thread_id: usize,
}

/// Memory access type
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum AccessType {
    Read,
    Write,
    ReadModifyWrite,
    Prefetch,
}

/// Memory access pattern type
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum AccessPatternType {
    Sequential,
    Random,
    Strided,
    Clustered,
    Temporal,
    Spatial,
}

/// Prediction model for memory access patterns
pub struct PredictionModel {
    pattern_type: AccessPatternType,
    coefficients: Vec<f64>,
    accuracy: f64,
    last_update: Instant,
}

/// Confidence tracking for predictions
pub struct ConfidenceTracker {
    successful_predictions: AtomicUsize,
    total_predictions: AtomicUsize,
    confidence_history: RwLock<VecDeque<f64>>,
}

/// Hardware prefetcher interface
pub struct HardwarePrefetcher {
    #[allow(dead_code)]
    capabilities: PlatformCapabilities,
    #[allow(dead_code)]
    prefetch_instructions: Vec<PrefetchInstruction>,
}

/// Prefetch instruction type
#[derive(Debug)]
pub struct PrefetchInstruction {
    instruction_type: PrefetchType,
    locality: Locality,
    distance: usize,
}

/// Prefetch type
#[derive(Debug, Clone, Copy)]
pub enum PrefetchType {
    T0,  // Temporal locality
    T1,  // Temporal locality with lower priority
    T2,  // Temporal locality with even lower priority
    NTA, // Non-temporal access
}

/// Cache locality hint
#[derive(Debug, Clone, Copy)]
pub enum Locality {
    High,
    Medium,
    Low,
    NonTemporal,
}

/// Access tracker for cache optimization
pub struct AccessTracker {
    #[allow(dead_code)]
    access_patterns: RwLock<HashMap<usize, AccessPattern>>,
    #[allow(dead_code)]
    hot_spots: RwLock<BTreeMap<usize, HotSpot>>,
    #[allow(dead_code)]
    cold_regions: RwLock<Vec<ColdRegion>>,
}

/// Access pattern for a memory region
#[derive(Debug)]
pub struct AccessPattern {
    region_start: usize,
    regionsize: usize,
    access_frequency: f64,
    access_type_distribution: HashMap<AccessType, f64>,
    temporal_locality: f64,
    spatial_locality: f64,
    last_access: Instant,
}

/// Hot memory region
#[derive(Debug)]
pub struct HotSpot {
    address: usize,
    size: usize,
    temperature: f64, // Access frequency metric
    last_access: Instant,
    access_count: usize,
}

/// Cold memory region
#[derive(Debug)]
pub struct ColdRegion {
    address: usize,
    size: usize,
    last_access: Instant,
    candidate_for_eviction: bool,
}

/// NUMA management system
pub struct NumaManager {
    #[allow(dead_code)]
    topology: NumaTopology,
    #[allow(dead_code)]
    binding_strategy: NumaBindingStrategy,
    #[allow(dead_code)]
    migration_engine: MigrationEngine,
    #[allow(dead_code)]
    affinity_manager: AffinityManager,
}

/// NUMA topology information
#[derive(Debug)]
pub struct NumaTopology {
    nodes: Vec<NumaNode>,
    distances: Array2<f64>,
    total_memory: usize,
}

/// NUMA node information
#[derive(Debug)]
pub struct NumaNode {
    node_id: usize,
    cpus: Vec<usize>,
    memorysize: usize,
    available_memory: AtomicUsize,
    local_bandwidth: f64,
    remote_bandwidth: f64,
}

/// Memory migration engine
pub struct MigrationEngine {
    migration_policy: NumaMigrationPolicy,
    migration_queue: Mutex<VecDeque<MigrationRequest>>,
    migration_stats: RwLock<MigrationStatistics>,
}

/// Memory migration request
#[derive(Debug)]
pub struct MigrationRequest {
    source_node: usize,
    target_node: usize,
    memory_region: MemoryRegion,
    priority: MigrationPriority,
    estimated_benefit: f64,
}

/// Memory region descriptor
#[derive(Debug)]
pub struct MemoryRegion {
    start_address: usize,
    size: usize,
    access_pattern: AccessPatternType,
    last_access: Instant,
}

/// Migration priority levels
#[derive(Debug, Clone, Copy, PartialOrd, Ord, PartialEq, Eq)]
pub enum MigrationPriority {
    Low,
    Medium,
    High,
    Critical,
}

/// Migration statistics
#[derive(Debug)]
pub struct MigrationStatistics {
    total_migrations: usize,
    successful_migrations: usize,
    average_benefit: f64,
    total_migration_time: Duration,
}

/// Thread affinity manager
pub struct AffinityManager {
    thread_assignments: RwLock<HashMap<usize, usize>>, // thread_id -> numa_node
    load_balancer: LoadBalancer,
}

/// Load balancer for NUMA nodes
pub struct LoadBalancer {
    node_loads: RwLock<Vec<f64>>,
    balancing_strategy: LoadBalancingStrategy,
}

/// Load balancing strategy
#[derive(Debug, Clone, Copy)]
pub enum LoadBalancingStrategy {
    RoundRobin,
    LeastLoaded,
    LocalityAware,
    Adaptive,
}

/// Predictive engine for memory management
pub struct PredictiveEngine {
    models: RwLock<HashMap<PredictiveModelType, Box<dyn PredictiveModel + Send + Sync>>>,
    feature_extractor: FeatureExtractor,
    trainingdata: RwLock<VecDeque<TrainingExample>>,
    model_performance: RwLock<HashMap<PredictiveModelType, ModelPerformance>>,
}

/// Predictive model trait
pub trait PredictiveModel: Send + Sync {
    fn predict(&self, features: &[f64]) -> f64;
    fn train(&mut self, trainingdata: &[TrainingExample]) -> Result<(), String>;
    fn get_confidence(&self) -> f64;
    fn get_feature_importance(&self) -> Vec<f64>;
}

/// Feature extractor for predictive models
pub struct FeatureExtractor {
    config: FeatureExtractionConfig,
    feature_cache: RwLock<HashMap<String, f64>>,
    normalization_params: RwLock<HashMap<String, (f64, f64)>>, // (mean, std)
}

/// Training example for predictive models
#[derive(Debug)]
pub struct TrainingExample {
    features: Vec<f64>,
    target: f64,
    timestamp: SystemTime,
    context: TrainingContext,
}

/// Training context for better model accuracy
#[derive(Debug)]
pub struct TrainingContext {
    operation_type: String,
    datasize: usize,
    thread_count: usize,
    system_load: f64,
}

/// Model performance metrics
#[derive(Debug)]
pub struct ModelPerformance {
    accuracy: f64,
    precision: f64,
    recall: f64,
    f1_score: f64,
    training_time: Duration,
    prediction_time: Duration,
}

/// Memory pressure monitoring system
pub struct PressureMonitor {
    thresholds: PressureThresholds,
    current_pressure: AtomicU64, // Fixed-point representation
    pressure_history: RwLock<VecDeque<PressureReading>>,
    response_engine: ResponseEngine,
}

/// Pressure reading
#[derive(Debug)]
pub struct PressureReading {
    pressure_level: f64,
    memory_usage: usize,
    swap_usage: usize,
    timestamp: Instant,
    trigger_events: Vec<PressureTrigger>,
}

/// Pressure trigger events
#[derive(Debug)]
pub enum PressureTrigger {
    AllocationFailure,
    SwapActivity,
    CacheEviction,
    PerformanceDegradation,
    SystemThrashing,
}

/// Pressure response engine
pub struct ResponseEngine {
    strategies: ResponseStrategies,
    active_responses: RwLock<Vec<ActiveResponse>>,
    response_queue: Mutex<VecDeque<PressureResponse>>,
}

/// Active pressure response
#[derive(Debug)]
pub struct ActiveResponse {
    response_type: PressureResponse,
    start_time: Instant,
    estimated_duration: Duration,
    effectiveness: f64,
}

/// Out-of-core processing manager
pub struct OutOfCoreManager {
    config: OutOfCoreConfig,
    chunk_scheduler: ChunkScheduler,
    storage_manager: StorageManager,
    compression_engine: CompressionEngine,
}

/// Chunk scheduler for out-of-core processing
pub struct ChunkScheduler {
    scheduling_strategy: ChunkSchedulingStrategy,
    active_chunks: RwLock<HashMap<usize, Chunk>>,
    chunk_queue: Mutex<VecDeque<ChunkRequest>>,
    priority_queue: Mutex<BTreeMap<u64, ChunkRequest>>,
}

/// Data chunk for out-of-core processing
#[derive(Debug)]
pub struct Chunk {
    chunk_id: usize,
    data_type: String,
    size: usize,
    location: ChunkLocation,
    access_count: AtomicUsize,
    last_access: RwLock<Instant>,
    compression_ratio: f64,
}

/// Chunk location
#[derive(Debug)]
pub enum ChunkLocation {
    Memory(usize),         // Memory address
    Disk(String),          // File path
    Network(String),       // Network URL
    Hybrid(usize, String), // Both memory and disk
}

/// Chunk request
#[derive(Debug)]
pub struct ChunkRequest {
    chunk_id: usize,
    request_type: ChunkRequestType,
    priority: u64,
    requester: usize, // Thread ID
    timestamp: Instant,
}

/// Chunk request type
#[derive(Debug, Clone, Copy)]
pub enum ChunkRequestType {
    Load,
    Evict,
    Prefetch,
    Store,
}

/// Storage manager for out-of-core data
pub struct StorageManager {
    storage_config: StorageConfig,
    file_manager: FileManager,
    network_manager: Option<NetworkManager>,
}

/// File manager for local storage
pub struct FileManager {
    storage_path: String,
    naming_strategy: NamingStrategy,
    file_handles: RwLock<HashMap<String, std::fs::File>>,
    fs_optimizer: FileSystemOptimizer,
}

/// File system optimizer
pub struct FileSystemOptimizer {
    fs_config: FileSystemConfig,
    io_scheduler: IOSchedulerManager,
    async_io_pool: Option<AsyncIOPool>,
}

/// I/O scheduler manager
pub struct IOSchedulerManager {
    scheduler_type: IOScheduler,
    queue_depth: usize,
    batchsize: usize,
}

/// Async I/O pool
pub struct AsyncIOPool {
    worker_threads: Vec<thread::JoinHandle<()>>,
    io_queue: Arc<Mutex<VecDeque<IORequest>>>,
    completion_queue: Arc<Mutex<VecDeque<IOCompletion>>>,
}

/// I/O request
#[derive(Debug)]
pub struct IORequest {
    request_id: u64,
    request_type: IORequestType,
    file_path: String,
    offset: u64,
    size: usize,
    buffer: Vec<u8>,
}

/// I/O request type
#[derive(Debug, Clone, Copy)]
pub enum IORequestType {
    Read,
    Write,
    Sync,
    ReadAhead,
}

/// I/O completion
#[derive(Debug)]
pub struct IOCompletion {
    request_id: u64,
    result: Result<usize, std::io::Error>,
    completion_time: Instant,
}

/// Network manager for distributed storage
pub struct NetworkManager {
    network_config: NetworkConfig,
    connection_pool: ConnectionPool,
}

/// Network configuration
#[derive(Debug)]
pub struct NetworkConfig {
    storage_nodes: Vec<StorageNode>,
    replication_factor: usize,
    consistency_level: ConsistencyLevel,
    timeout: Duration,
}

/// Storage node information
#[derive(Debug)]
pub struct StorageNode {
    node_id: String,
    address: String,
    port: u16,
    capacity: usize,
    latency: Duration,
    bandwidth: f64,
}

/// Consistency level for distributed storage
#[derive(Debug, Clone, Copy)]
pub enum ConsistencyLevel {
    One,
    Quorum,
    All,
    LocalQuorum,
    EachQuorum,
}

/// Connection pool for network storage
pub struct ConnectionPool {
    connections: RwLock<HashMap<String, Connection>>,
    max_connections: usize,
    connection_timeout: Duration,
}

/// Network connection
pub struct Connection {
    node_id: String,
    last_used: Instant,
    active_requests: AtomicUsize,
}

/// Compression engine for storage optimization
pub struct CompressionEngine {
    config: CompressionConfig,
    compressors: HashMap<CompressionAlgorithm, Box<dyn Compressor + Send + Sync>>,
    compression_stats: RwLock<CompressionStatistics>,
}

/// Compressor trait
pub trait Compressor: Send + Sync {
    fn compress(&self, data: &[u8]) -> Result<Vec<u8>, String>;
    fn decompress(&self, data: &[u8]) -> Result<Vec<u8>, String>;
    fn compression_ratio(&self, originalsize: usize, compressedsize: usize) -> f64;
}

/// Compression statistics
#[derive(Debug)]
pub struct CompressionStatistics {
    total_compressions: usize,
    total_decompressions: usize,
    total_bytes_compressed: usize,
    total_bytes_decompressed: usize,
    average_compression_ratio: f64,
    compression_time: Duration,
    decompression_time: Duration,
}

/// Garbage collection manager
pub struct GCManager {
    config: GarbageCollectionConfig,
    gc_scheduler: GCScheduler,
    reference_tracker: ReferenceTracker,
    workload_analyzer: WorkloadAnalyzer,
}

/// GC scheduler
pub struct GCScheduler {
    gc_strategy: GCStrategy,
    trigger_conditions: GCTriggerConditions,
    gc_queue: Mutex<VecDeque<GCTask>>,
    gc_statistics: RwLock<GCStatistics>,
}

/// GC task
#[derive(Debug)]
pub struct GCTask {
    task_type: GCTaskType,
    priority: GCPriority,
    estimated_duration: Duration,
    memory_regions: Vec<MemoryRegion>,
}

/// GC task type
#[derive(Debug, Clone, Copy)]
pub enum GCTaskType {
    MarkAndSweep,
    ReferenceCounting,
    Generational,
    Incremental,
    Concurrent,
}

/// GC priority
#[derive(Debug, Clone, Copy, PartialOrd, Ord, PartialEq, Eq)]
pub enum GCPriority {
    Low,
    Normal,
    High,
    Emergency,
}

/// GC statistics
#[derive(Debug)]
pub struct GCStatistics {
    total_collections: usize,
    total_pause_time: Duration,
    average_pause_time: Duration,
    memory_reclaimed: usize,
    collection_frequency: f64,
}

/// Reference tracker for GC
pub struct ReferenceTracker {
    reference_counts: RwLock<HashMap<usize, usize>>,
    weak_references: RwLock<HashMap<usize, Vec<Weak<()>>>>,
    gc_roots: RwLock<Vec<usize>>,
}

/// Statistical workload analyzer for GC optimization
pub struct WorkloadAnalyzer {
    workload_config: GCWorkloadAwareness,
    operation_tracker: OperationTracker,
    lifecycle_analyzer: LifecycleAnalyzer,
    phase_detector: PhaseDetector,
}

/// Operation tracker for workload analysis
pub struct OperationTracker {
    current_operations: RwLock<HashMap<usize, StatisticalOperation>>,
    operation_history: RwLock<VecDeque<CompletedOperation>>,
}

/// Statistical operation
#[derive(Debug)]
pub struct StatisticalOperation {
    operation_type: StatOperationType,
    start_time: Instant,
    datasize: usize,
    memory_usage: usize,
    thread_id: usize,
}

/// Statistical operation type
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum StatOperationType {
    DescriptiveStats,
    Correlation,
    Regression,
    DistributionFitting,
    HypothesisTesting,
    MCMC,
    Bayesian,
    Multivariate,
    TimeSeries,
    Survival,
    Clustering,
    Classification,
}

/// Completed operation for analysis
#[derive(Debug)]
pub struct CompletedOperation {
    operation: StatisticalOperation,
    completion_time: Instant,
    peak_memory: usize,
    gc_triggered: bool,
}

/// Lifecycle analyzer for memory objects
pub struct LifecycleAnalyzer {
    object_lifetimes: RwLock<HashMap<usize, ObjectLifetime>>,
    lifetime_patterns: RwLock<HashMap<StatOperationType, LifetimePattern>>,
}

/// Object lifetime information
#[derive(Debug)]
pub struct ObjectLifetime {
    object_id: usize,
    creation_time: Instant,
    last_access: Instant,
    access_count: usize,
    size: usize,
    object_type: ObjectType,
}

/// Object type for lifetime analysis
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum ObjectType {
    InputData,
    IntermediateResult,
    FinalResult,
    TemporaryData,
    CachedData,
    MetaData,
}

/// Lifetime pattern for different operations
#[derive(Debug)]
pub struct LifetimePattern {
    operation_type: StatOperationType,
    average_lifetime: Duration,
    lifetime_variance: Duration,
    access_pattern: AccessPatternType,
    memory_usage_curve: Vec<(Duration, f64)>,
}

/// Computation phase detector
pub struct PhaseDetector {
    current_phase: RwLock<ComputationPhase>,
    phase_history: RwLock<VecDeque<PhaseTransition>>,
    phase_predictor: PhasePredictor,
}

/// Computation phase
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum ComputationPhase {
    Initialization,
    DataLoading,
    Preprocessing,
    Computation,
    Postprocessing,
    ResultGeneration,
    Cleanup,
}

/// Phase transition information
#[derive(Debug)]
pub struct PhaseTransition {
    from_phase: ComputationPhase,
    to_phase: ComputationPhase,
    transition_time: Instant,
    memory_delta: i64,
    gc_activity: bool,
}

/// Phase predictor for memory optimization
pub struct PhasePredictor {
    transition_model: TransitionModel,
    prediction_confidence: f64,
}

/// Transition model for phase prediction
pub struct TransitionModel {
    transition_probabilities: HashMap<(ComputationPhase, ComputationPhase), f64>,
    state_durations: HashMap<ComputationPhase, Duration>,
}

/// Performance monitor for memory operations
pub struct MemoryPerformanceMonitor {
    performance_metrics: RwLock<MemoryPerformanceMetrics>,
    metric_history: RwLock<VecDeque<MemoryPerformanceSnapshot>>,
    alerting_system: AlertingSystem,
}

/// Memory performance metrics
#[derive(Debug, Clone)]
pub struct MemoryPerformanceMetrics {
    allocation_rate: f64,        // allocations per second
    deallocation_rate: f64,      // deallocations per second
    memory_bandwidth: f64,       // GB/s
    cache_hit_ratio: f64,        // 0.0 to 1.0
    numa_locality: f64,          // 0.0 to 1.0
    gc_overhead: f64,            // percentage of time spent in GC
    fragmentation_ratio: f64,    // 0.0 to 1.0
    pressure_level: f64,         // 0.0 to 1.0
    out_of_core_efficiency: f64, // 0.0 to 1.0
    prediction_accuracy: f64,    // 0.0 to 1.0
}

/// Memory performance snapshot
#[derive(Debug)]
pub struct MemoryPerformanceSnapshot {
    timestamp: Instant,
    metrics: MemoryPerformanceMetrics,
    system_context: SystemContext,
}

/// System context for performance analysis
#[derive(Debug)]
pub struct SystemContext {
    cpu_usage: f64,
    system_load: f64,
    disk_io_rate: f64,
    network_io_rate: f64,
    temperature: f64,
    power_consumption: f64,
}

/// Alerting system for memory issues
pub struct AlertingSystem {
    alert_rules: Vec<AlertRule>,
    active_alerts: RwLock<Vec<ActiveAlert>>,
    alert_history: RwLock<VecDeque<AlertEvent>>,
}

/// Alert rule configuration
#[derive(Debug)]
pub struct AlertRule {
    rule_id: String,
    condition: AlertCondition,
    severity: AlertSeverity,
    cooldown_period: Duration,
    action: AlertAction,
}

/// Alert condition
pub enum AlertCondition {
    MemoryUsageThreshold(f64),
    CacheHitRatioThreshold(f64),
    GCOverheadThreshold(f64),
    FragmentationThreshold(f64),
    PressureLevelThreshold(f64),
    PerformanceDegradation(f64),
    Custom(Box<dyn Fn(&MemoryPerformanceMetrics) -> bool + Send + Sync>),
}

impl std::fmt::Debug for AlertCondition {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            AlertCondition::MemoryUsageThreshold(v) => {
                f.debug_tuple("MemoryUsageThreshold").field(v).finish()
            }
            AlertCondition::CacheHitRatioThreshold(v) => {
                f.debug_tuple("CacheHitRatioThreshold").field(v).finish()
            }
            AlertCondition::GCOverheadThreshold(v) => {
                f.debug_tuple("GCOverheadThreshold").field(v).finish()
            }
            AlertCondition::FragmentationThreshold(v) => {
                f.debug_tuple("FragmentationThreshold").field(v).finish()
            }
            AlertCondition::PressureLevelThreshold(v) => {
                f.debug_tuple("PressureLevelThreshold").field(v).finish()
            }
            AlertCondition::PerformanceDegradation(v) => {
                f.debug_tuple("PerformanceDegradation").field(v).finish()
            }
            AlertCondition::Custom(_) => f.debug_tuple("Custom").field(&"<function>").finish(),
        }
    }
}

/// Alert severity level
#[derive(Debug, Clone, Copy, PartialOrd, Ord, PartialEq, Eq)]
pub enum AlertSeverity {
    Info,
    Warning,
    Error,
    Critical,
}

/// Alert action
#[derive(Debug)]
pub enum AlertAction {
    Log(String),
    Notify(String),
    TriggerGC,
    ReduceMemoryUsage,
    EnableOutOfCore,
    Emergency,
    Custom(String),
}

/// Active alert
#[derive(Debug)]
pub struct ActiveAlert {
    rule_id: String,
    start_time: Instant,
    last_trigger: Instant,
    trigger_count: usize,
    acknowledged: bool,
}

/// Alert event for history tracking
#[derive(Debug)]
pub struct AlertEvent {
    rule_id: String,
    timestamp: Instant,
    severity: AlertSeverity,
    message: String,
    resolved: bool,
    resolution_time: Option<Instant>,
}

/// Allocation context for decision making
#[derive(Debug)]
struct AllocationContext {
    size: usize,
    thread_id: usize,
    current_pressure: f64,
    predicted_usage: f64,
    numa_node: Option<usize>,
    allocation_type: AllocationType,
    urgency: AllocationUrgency,
}

/// Type of allocation
#[derive(Debug, Clone, Copy)]
enum AllocationType {
    SmallObject,
    LargeObject,
    HugeObject,
    TemporaryData,
    PersistentData,
    SharedData,
}

/// Urgency level for allocation
#[derive(Debug, Clone, Copy, PartialOrd, Ord, PartialEq, Eq)]
enum AllocationUrgency {
    Low,
    Normal,
    High,
    Critical,
}

impl<F> AdaptiveMemoryManager<F>
where
    F: Float
        + NumCast
        + SimdUnifiedOps
        + Zero
        + One
        + PartialOrd
        + Copy
        + Send
        + Sync
        + 'static
        + std::fmt::Display,
{
    /// Create new adaptive memory manager
    pub fn new() -> Self {
        Self::with_config(AdaptiveMemoryConfig::default())
    }

    /// Create with custom configuration
    pub fn with_config(config: AdaptiveMemoryConfig) -> Self {
        let memory_pools = Arc::new(RwLock::new(HashMap::new()));
        let cache_manager = Arc::new(CacheManager::new(&config.cache_optimization));
        let numa_manager = Arc::new(NumaManager::new(&config.numa_config));
        let predictive_engine = Arc::new(PredictiveEngine::new(&config.predictive_config));
        let pressure_monitor = Arc::new(PressureMonitor::new(&config.pressure_config));
        let out_of_core_manager = Arc::new(OutOfCoreManager::new(&config.out_of_core_config));
        let gc_manager = Arc::new(GCManager::new(&config.gc_config));
        let performance_monitor = Arc::new(MemoryPerformanceMonitor::new());

        Self {
            config,
            memory_pools,
            cache_manager,
            numa_manager,
            predictive_engine,
            pressure_monitor,
            out_of_core_manager,
            gc_manager,
            performance_monitor,
            _phantom: PhantomData,
        }
    }

    /// Allocate memory with optimal strategy
    pub fn allocate(&self, size: usize) -> StatsResult<*mut u8> {
        // Analyze allocation request
        let allocation_context = self.analyze_allocation_request(size)?;

        // Select optimal allocation strategy
        let strategy = self.select_allocation_strategy(&allocation_context)?;

        // Perform allocation
        match strategy {
            AllocationStrategy::System => self.allocate_system(size),
            AllocationStrategy::Pool => self.allocate_pool(size),
            AllocationStrategy::NumaAware => self.allocate_numa_aware(size, &allocation_context),
            AllocationStrategy::MemoryMapped => self.allocate_memory_mapped(size),
            AllocationStrategy::Adaptive => self.allocate_adaptive(size, &allocation_context),
            AllocationStrategy::ZeroCopy => self.allocate_zero_copy(size),
        }
    }

    /// Analyze allocation request context
    fn analyze_allocation_request(&self, size: usize) -> StatsResult<AllocationContext> {
        let current_thread = thread::current().id();
        let thread_id = unsafe { std::mem::transmute::<_, usize>(current_thread) };

        let current_pressure = self.pressure_monitor.get_current_pressure();
        let predicted_usage = self
            .predictive_engine
            .predict_memory_usage(size, thread_id)?;
        let numa_node = self.numa_manager.get_optimal_node(thread_id);

        Ok(AllocationContext {
            size,
            thread_id,
            current_pressure,
            predicted_usage,
            numa_node,
            allocation_type: self.infer_allocation_type(size),
            urgency: self.calculate_urgency(size, current_pressure),
        })
    }

    /// Infer allocation type from size and context
    fn infer_allocation_type(&self, size: usize) -> AllocationType {
        if size < 1024 {
            AllocationType::SmallObject
        } else if size < 1024 * 1024 {
            AllocationType::LargeObject
        } else if size < 1024 * 1024 * 1024 {
            AllocationType::HugeObject
        } else {
            AllocationType::HugeObject
        }
    }

    /// Calculate allocation urgency
    fn calculate_urgency(&self, size: usize, pressure: f64) -> AllocationUrgency {
        if pressure > 0.95 {
            AllocationUrgency::Critical
        } else if pressure > 0.85 {
            AllocationUrgency::High
        } else if pressure > 0.7 {
            AllocationUrgency::Normal
        } else {
            AllocationUrgency::Low
        }
    }

    /// Select optimal allocation strategy
    fn select_allocation_strategy(
        &self,
        context: &AllocationContext,
    ) -> StatsResult<AllocationStrategy> {
        match self.config.allocation_strategy {
            AllocationStrategy::Adaptive => {
                // Use ML model to select best strategy
                let features = self.extract_allocation_features(context);
                let predicted_strategy = self
                    .predictive_engine
                    .predict_allocation_strategy(&features)?;
                Ok(predicted_strategy)
            }
            strategy => Ok(strategy),
        }
    }

    /// Extract features for allocation strategy prediction
    fn extract_allocation_features(&self, context: &AllocationContext) -> Vec<f64> {
        vec![
            context.size as f64,
            context.current_pressure,
            context.predicted_usage,
            context.numa_node.unwrap_or(0) as f64,
            context.allocation_type as u8 as f64,
            context.urgency as u8 as f64,
        ]
    }

    /// System allocator
    fn allocate_system(&self, size: usize) -> StatsResult<*mut u8> {
        use std::alloc::{alloc, Layout};

        let layout = Layout::from_size_align(size, std::mem::align_of::<F>())
            .map_err(|e| StatsError::InvalidArgument(format!("Invalid layout: {}", e)))?;

        let ptr = unsafe { alloc(layout) };
        if ptr.is_null() {
            Err(StatsError::ComputationError(
                "Memory allocation failed".to_string(),
            ))
        } else {
            Ok(ptr)
        }
    }

    /// Pool allocator
    fn allocate_pool(&self, size: usize) -> StatsResult<*mut u8> {
        // Get or create appropriate memory pool
        let poolsize = self.calculate_poolsize(size);
        let pool = self.get_or_create_pool(poolsize)?;

        // Allocate from pool
        pool.allocate()
    }

    /// Calculate appropriate pool size for allocation
    fn calculate_poolsize(&self, size: usize) -> usize {
        // Round up to next power of 2
        let mut poolsize = 1;
        while poolsize < size {
            poolsize *= 2;
        }
        poolsize
    }

    /// Get or create memory pool
    fn get_or_create_pool(&self, poolsize: usize) -> StatsResult<Arc<MemoryPool>> {
        {
            let pools = self.memory_pools.read().unwrap();
            if let Some(pool) = pools.get(&poolsize) {
                return Ok(Arc::clone(pool));
            }
        }

        // Create new pool
        let mut pools = self.memory_pools.write().unwrap();
        if let Some(pool) = pools.get(&poolsize) {
            return Ok(Arc::clone(pool));
        }

        let pool = Arc::new(MemoryPool::new(poolsize, self.config.allocation_strategy));
        pools.insert(poolsize, Arc::clone(&pool));
        Ok(pool)
    }

    /// NUMA-aware allocator
    fn allocate_numa_aware(
        &self,
        size: usize,
        context: &AllocationContext,
    ) -> StatsResult<*mut u8> {
        let numa_node = context.numa_node.unwrap_or(0);
        self.numa_manager.allocate_on_node(size, numa_node)
    }

    /// Memory-mapped allocator
    fn allocate_memory_mapped(&self, size: usize) -> StatsResult<*mut u8> {
        self.out_of_core_manager.allocate_mapped(size)
    }

    /// Adaptive allocator
    fn allocate_adaptive(&self, size: usize, context: &AllocationContext) -> StatsResult<*mut u8> {
        // Use real-time performance feedback to select strategy
        let performance_metrics = self.performance_monitor.get_current_metrics();

        if performance_metrics.memory_bandwidth < 0.5 {
            // Low bandwidth - use pool allocation
            self.allocate_pool(size)
        } else if performance_metrics.numa_locality < 0.7 {
            // Poor NUMA locality - use NUMA-aware allocation
            self.allocate_numa_aware(size, context)
        } else if performance_metrics.cache_hit_ratio < 0.8 {
            // Poor cache performance - use system allocation
            self.allocate_system(size)
        } else {
            // Good performance - use pool allocation
            self.allocate_pool(size)
        }
    }

    /// Zero-copy allocator
    fn allocate_zero_copy(&self, size: usize) -> StatsResult<*mut u8> {
        // Implement zero-copy allocation using memory mapping
        self.allocate_memory_mapped(size)
    }

    /// Deallocate memory
    pub fn deallocate(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        // Determine allocation strategy used for this pointer
        let strategy = self.infer_deallocation_strategy(ptr, size);

        match strategy {
            AllocationStrategy::System => self.deallocate_system(ptr, size),
            AllocationStrategy::Pool => self.deallocate_pool(ptr, size),
            AllocationStrategy::NumaAware => self.deallocate_numa_aware(ptr, size),
            AllocationStrategy::MemoryMapped => self.deallocate_memory_mapped(ptr, size),
            AllocationStrategy::Adaptive => self.deallocate_adaptive(ptr, size),
            AllocationStrategy::ZeroCopy => self.deallocate_zero_copy(ptr, size),
        }
    }

    /// Infer deallocation strategy from pointer
    fn infer_deallocation_strategy(&self, ptr: *mut u8, size: usize) -> AllocationStrategy {
        // Simplified - would use metadata to track allocation strategy
        self.config.allocation_strategy
    }

    /// System deallocation
    fn deallocate_system(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        use std::alloc::{dealloc, Layout};

        let layout = Layout::from_size_align(size, std::mem::align_of::<F>())
            .map_err(|e| StatsError::InvalidArgument(format!("Invalid layout: {}", e)))?;

        unsafe { dealloc(ptr, layout) };
        Ok(())
    }

    /// Pool deallocation
    fn deallocate_pool(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        let poolsize = self.calculate_poolsize(size);
        if let Some(pool) = self.memory_pools.read().unwrap().get(&poolsize) {
            pool.deallocate(ptr)
        } else {
            Err(StatsError::InvalidArgument("Pool not found".to_string()))
        }
    }

    /// NUMA-aware deallocation
    fn deallocate_numa_aware(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        self.numa_manager.deallocate(ptr, size)
    }

    /// Memory-mapped deallocation
    fn deallocate_memory_mapped(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        self.out_of_core_manager.deallocate_mapped(ptr, size)
    }

    /// Adaptive deallocation
    fn deallocate_adaptive(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        // Use the same strategy as allocation
        self.deallocate_system(ptr, size)
    }

    /// Zero-copy deallocation
    fn deallocate_zero_copy(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        self.deallocate_memory_mapped(ptr, size)
    }

    /// Optimize memory layout for better cache performance
    pub fn optimize_layout<T>(&self, data: &mut ArrayView2<T>) -> StatsResult<()>
    where
        T: Clone + Send + Sync,
    {
        self.cache_manager.optimize_layout(data)
    }

    /// Trigger garbage collection
    pub fn trigger_gc(&self) -> StatsResult<GCResult> {
        self.gc_manager.trigger_collection()
    }

    /// Get performance metrics
    pub fn get_performance_metrics(&self) -> MemoryPerformanceMetrics {
        self.performance_monitor.get_current_metrics()
    }

    /// Update configuration
    pub fn update_config(&mut self, config: AdaptiveMemoryConfig) {
        self.config = config;
    }

    /// Get memory usage statistics
    pub fn get_memory_stats(&self) -> MemoryUsageStatistics {
        MemoryUsageStatistics {
            total_allocated: self.calculate_total_allocated(),
            peak_allocated: self.calculate_peak_allocated(),
            fragmentation_ratio: self.calculate_fragmentation(),
            cache_hit_ratio: self.cache_manager.get_hit_ratio(),
            numa_efficiency: self.numa_manager.get_efficiency(),
            gc_overhead: self.gc_manager.get_overhead(),
            pressure_level: self.pressure_monitor.get_current_pressure(),
            out_of_core_ratio: self.out_of_core_manager.get_ratio(),
        }
    }

    /// Calculate total allocated memory
    fn calculate_total_allocated(&self) -> usize {
        self.memory_pools
            .read()
            .unwrap()
            .values()
            .map(|pool| pool.get_allocatedsize())
            .sum()
    }

    /// Calculate peak allocated memory
    fn calculate_peak_allocated(&self) -> usize {
        self.memory_pools
            .read()
            .unwrap()
            .values()
            .map(|pool| pool.get_peaksize())
            .max()
            .unwrap_or(0)
    }

    /// Calculate memory fragmentation ratio
    fn calculate_fragmentation(&self) -> f64 {
        let total_allocated = self.calculate_total_allocated() as f64;
        let total_requested = self.calculate_total_requested() as f64;

        if total_requested > 0.0 {
            (total_allocated - total_requested) / total_allocated
        } else {
            0.0
        }
    }

    /// Calculate total requested memory
    fn calculate_total_requested(&self) -> usize {
        // Simplified - would track actual requested sizes
        self.calculate_total_allocated()
    }
}

/// Memory usage statistics
#[derive(Debug)]
pub struct MemoryUsageStatistics {
    pub total_allocated: usize,
    pub peak_allocated: usize,
    pub fragmentation_ratio: f64,
    pub cache_hit_ratio: f64,
    pub numa_efficiency: f64,
    pub gc_overhead: f64,
    pub pressure_level: f64,
    pub out_of_core_ratio: f64,
}

/// GC result information
#[derive(Debug)]
pub struct GCResult {
    pub memory_reclaimed: usize,
    pub collection_time: Duration,
    pub objects_collected: usize,
    pub fragmentation_reduced: f64,
}

impl MemoryPool {
    fn new(_chunksize: usize, strategy: AllocationStrategy) -> Self {
        Self {
            chunksize: _chunksize,
            available_chunks: Mutex::new(VecDeque::new()),
            allocated_chunks: AtomicUsize::new(0),
            total_chunks: AtomicUsize::new(0),
            allocation_strategy: strategy,
            numa_node: None,
        }
    }

    fn allocate(&self) -> StatsResult<*mut u8> {
        // Try to get chunk from available pool
        {
            let mut available = self.available_chunks.lock().unwrap();
            if let Some(ptr) = available.pop_front() {
                self.allocated_chunks.fetch_add(1, Ordering::Relaxed);
                return Ok(ptr);
            }
        }

        // No available chunks, allocate new one
        self.allocate_new_chunk()
    }

    fn allocate_new_chunk(&self) -> StatsResult<*mut u8> {
        use std::alloc::{alloc, Layout};

        let layout = Layout::from_size_align(self.chunksize, 64) // 64-byte alignment for SIMD
            .map_err(|e| StatsError::InvalidArgument(format!("Invalid layout: {}", e)))?;

        let ptr = unsafe { alloc(layout) };
        if ptr.is_null() {
            Err(StatsError::ComputationError(
                "Memory allocation failed".to_string(),
            ))
        } else {
            self.allocated_chunks.fetch_add(1, Ordering::Relaxed);
            self.total_chunks.fetch_add(1, Ordering::Relaxed);
            Ok(ptr)
        }
    }

    fn deallocate(&self, ptr: *mut u8) -> StatsResult<()> {
        let mut available = self.available_chunks.lock().unwrap();
        available.push_back(ptr);
        self.allocated_chunks.fetch_sub(1, Ordering::Relaxed);
        Ok(())
    }

    fn get_allocatedsize(&self) -> usize {
        self.allocated_chunks.load(Ordering::Relaxed) * self.chunksize
    }

    fn get_peaksize(&self) -> usize {
        self.total_chunks.load(Ordering::Relaxed) * self.chunksize
    }
}

// Implement stub methods for other managers to avoid compilation errors
impl CacheManager {
    fn new(config: &CacheOptimizationConfig) -> Self {
        Self {
            cache_hierarchy: config.cache_hierarchy.clone(),
            layout_optimizer: LayoutOptimizer::new(),
            prefetch_engine: PrefetchEngine::new(&config.prefetch_config),
            access_tracker: AccessTracker::new(),
        }
    }

    fn optimize_layout<T>(&self, data: &mut ArrayView2<T>) -> StatsResult<()>
    where
        T: Clone + Send + Sync,
    {
        // Stub implementation
        Ok(())
    }

    fn get_hit_ratio(&self) -> f64 {
        0.9 // Stub value
    }
}

impl LayoutOptimizer {
    fn new() -> Self {
        Self {
            current_strategy: RwLock::new(DataLayoutStrategy::Adaptive),
            performance_history: RwLock::new(VecDeque::new()),
            adaptive_threshold: 0.8,
        }
    }
}

impl PrefetchEngine {
    fn new(config: &PrefetchConfig) -> Self {
        Self {
            prefetch_config: config.clone(),
            pattern_predictor: PatternPredictor::new(),
            hardware_prefetcher: HardwarePrefetcher::new(),
        }
    }
}

impl PatternPredictor {
    fn new() -> Self {
        Self {
            access_history: RwLock::new(VecDeque::new()),
            pattern_models: RwLock::new(HashMap::new()),
            confidence_tracker: ConfidenceTracker::new(),
        }
    }
}

impl ConfidenceTracker {
    fn new() -> Self {
        Self {
            successful_predictions: AtomicUsize::new(0),
            total_predictions: AtomicUsize::new(0),
            confidence_history: RwLock::new(VecDeque::new()),
        }
    }
}

impl HardwarePrefetcher {
    fn new() -> Self {
        Self {
            capabilities: PlatformCapabilities::detect(),
            prefetch_instructions: Vec::new(),
        }
    }
}

impl AccessTracker {
    fn new() -> Self {
        Self {
            access_patterns: RwLock::new(HashMap::new()),
            hot_spots: RwLock::new(BTreeMap::new()),
            cold_regions: RwLock::new(Vec::new()),
        }
    }
}

impl NumaManager {
    fn new(config: &NumaConfig) -> Self {
        Self {
            topology: NumaTopology::detect(),
            binding_strategy: config.binding_strategy.clone(),
            migration_engine: MigrationEngine::new(config.migration_policy),
            affinity_manager: AffinityManager::new(),
        }
    }

    fn get_optimal_node(&self, size: usize) -> Option<usize> {
        // Stub implementation
        Some(0)
    }

    fn allocate_on_node(&self, size: usize, node: usize) -> StatsResult<*mut u8> {
        // Fallback to system allocation for now
        use std::alloc::{alloc, Layout};

        let layout = Layout::from_size_align(size, 8)
            .map_err(|e| StatsError::InvalidArgument(format!("Invalid layout: {}", e)))?;

        let ptr = unsafe { alloc(layout) };
        if ptr.is_null() {
            Err(StatsError::ComputationError(
                "Memory allocation failed".to_string(),
            ))
        } else {
            Ok(ptr)
        }
    }

    fn deallocate(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        use std::alloc::{dealloc, Layout};

        let layout = Layout::from_size_align(size, 8)
            .map_err(|e| StatsError::InvalidArgument(format!("Invalid layout: {}", e)))?;

        unsafe { dealloc(ptr, layout) };
        Ok(())
    }

    fn get_efficiency(&self) -> f64 {
        0.85 // Stub value
    }
}

impl NumaTopology {
    fn detect() -> Self {
        Self {
            nodes: vec![NumaNode {
                node_id: 0,
                cpus: (0..num_threads()).collect(),
                memorysize: 16 * 1024 * 1024 * 1024, // 16GB
                available_memory: AtomicUsize::new(12 * 1024 * 1024 * 1024), // 12GB available
                local_bandwidth: 50.0,
                remote_bandwidth: 25.0,
            }],
            distances: Array2::zeros((1, 1)),
            total_memory: 16 * 1024 * 1024 * 1024,
        }
    }
}

impl MigrationEngine {
    fn new(policy: NumaMigrationPolicy) -> Self {
        Self {
            migration_policy: policy,
            migration_queue: Mutex::new(VecDeque::new()),
            migration_stats: RwLock::new(MigrationStatistics {
                total_migrations: 0,
                successful_migrations: 0,
                average_benefit: 0.0,
                total_migration_time: Duration::from_secs(0),
            }),
        }
    }
}

impl AffinityManager {
    fn new() -> Self {
        Self {
            thread_assignments: RwLock::new(HashMap::new()),
            load_balancer: LoadBalancer::new(),
        }
    }
}

impl LoadBalancer {
    fn new() -> Self {
        Self {
            node_loads: RwLock::new(vec![0.0]),
            balancing_strategy: LoadBalancingStrategy::Adaptive,
        }
    }
}

impl PredictiveEngine {
    fn new(config: &PredictiveConfig) -> Self {
        Self {
            models: RwLock::new(HashMap::new()),
            feature_extractor: FeatureExtractor::new(&config.feature_config),
            trainingdata: RwLock::new(VecDeque::new()),
            model_performance: RwLock::new(HashMap::new()),
        }
    }

    fn predict_memory_usage(&self, size: usize, _threadid: usize) -> StatsResult<f64> {
        // Stub implementation - simple linear prediction
        Ok(size as f64 * 1.2) // Assume 20% overhead
    }

    fn predict_allocation_strategy(&self, data: &[f64]) -> StatsResult<AllocationStrategy> {
        // Stub implementation
        Ok(AllocationStrategy::Pool)
    }
}

impl FeatureExtractor {
    fn new(config: &FeatureExtractionConfig) -> Self {
        Self {
            config: config.clone(),
            feature_cache: RwLock::new(HashMap::new()),
            normalization_params: RwLock::new(HashMap::new()),
        }
    }
}

impl PressureMonitor {
    fn new(config: &MemoryPressureConfig) -> Self {
        Self {
            thresholds: config.pressure_thresholds.clone(),
            current_pressure: AtomicU64::new(0),
            pressure_history: RwLock::new(VecDeque::new()),
            response_engine: ResponseEngine::new(&config.response_strategies),
        }
    }

    fn get_current_pressure(&self) -> f64 {
        let pressure_bits = self.current_pressure.load(Ordering::Relaxed);
        f64::from_bits(pressure_bits)
    }
}

impl ResponseEngine {
    fn new(strategies: &ResponseStrategies) -> Self {
        Self {
            strategies: strategies.clone(),
            active_responses: RwLock::new(Vec::new()),
            response_queue: Mutex::new(VecDeque::new()),
        }
    }
}

impl OutOfCoreManager {
    fn new(config: &OutOfCoreConfig) -> Self {
        Self {
            config: config.clone(),
            chunk_scheduler: ChunkScheduler::new(config.scheduling_strategy),
            storage_manager: StorageManager::new(&config.storage_config),
            compression_engine: CompressionEngine::new(&config.compression_config),
        }
    }

    fn allocate_mapped(&self, size: usize) -> StatsResult<*mut u8> {
        // Stub implementation - fallback to system allocation
        use std::alloc::{alloc, Layout};

        let layout = Layout::from_size_align(size, 8)
            .map_err(|e| StatsError::InvalidArgument(format!("Invalid layout: {}", e)))?;

        let ptr = unsafe { alloc(layout) };
        if ptr.is_null() {
            Err(StatsError::ComputationError(
                "Memory allocation failed".to_string(),
            ))
        } else {
            Ok(ptr)
        }
    }

    fn deallocate_mapped(&self, ptr: *mut u8, size: usize) -> StatsResult<()> {
        use std::alloc::{dealloc, Layout};

        let layout = Layout::from_size_align(size, 8)
            .map_err(|e| StatsError::InvalidArgument(format!("Invalid layout: {}", e)))?;

        unsafe { dealloc(ptr, layout) };
        Ok(())
    }

    fn get_ratio(&self) -> f64 {
        0.1 // Stub value - 10% out-of-core usage
    }
}

impl ChunkScheduler {
    fn new(strategy: ChunkSchedulingStrategy) -> Self {
        Self {
            scheduling_strategy: strategy,
            active_chunks: RwLock::new(HashMap::new()),
            chunk_queue: Mutex::new(VecDeque::new()),
            priority_queue: Mutex::new(BTreeMap::new()),
        }
    }
}

impl StorageManager {
    fn new(config: &StorageConfig) -> Self {
        Self {
            storage_config: config.clone(),
            file_manager: FileManager::new(config),
            network_manager: None,
        }
    }
}

impl FileManager {
    fn new(config: &StorageConfig) -> Self {
        Self {
            storage_path: config.storage_path.clone(),
            naming_strategy: config.naming_strategy,
            file_handles: RwLock::new(HashMap::new()),
            fs_optimizer: FileSystemOptimizer::new(&config.fs_optimization),
        }
    }
}

impl FileSystemOptimizer {
    fn new(config: &FileSystemConfig) -> Self {
        Self {
            fs_config: config.clone(),
            io_scheduler: IOSchedulerManager::new(config.io_scheduler),
            async_io_pool: None,
        }
    }
}

impl IOSchedulerManager {
    fn new(_schedulertype: IOScheduler) -> Self {
        Self {
            scheduler_type: _schedulertype,
            queue_depth: 32,
            batchsize: 16,
        }
    }
}

impl CompressionEngine {
    fn new(config: &CompressionConfig) -> Self {
        Self {
            config: config.clone(),
            compressors: HashMap::new(),
            compression_stats: RwLock::new(CompressionStatistics {
                total_compressions: 0,
                total_decompressions: 0,
                total_bytes_compressed: 0,
                total_bytes_decompressed: 0,
                average_compression_ratio: 0.0,
                compression_time: Duration::from_secs(0),
                decompression_time: Duration::from_secs(0),
            }),
        }
    }
}

impl GCManager {
    fn new(config: &GarbageCollectionConfig) -> Self {
        Self {
            config: config.clone(),
            gc_scheduler: GCScheduler::new(config),
            reference_tracker: ReferenceTracker::new(),
            workload_analyzer: WorkloadAnalyzer::new(&config.workload_awareness),
        }
    }

    fn trigger_collection(&self) -> StatsResult<GCResult> {
        // Stub implementation
        Ok(GCResult {
            memory_reclaimed: 1024 * 1024, // 1MB
            collection_time: Duration::from_millis(10),
            objects_collected: 100,
            fragmentation_reduced: 0.1,
        })
    }

    fn get_overhead(&self) -> f64 {
        0.05 // 5% GC overhead
    }
}

impl GCScheduler {
    fn new(config: &GarbageCollectionConfig) -> Self {
        Self {
            gc_strategy: config.gc_strategy,
            trigger_conditions: config.trigger_conditions.clone(),
            gc_queue: Mutex::new(VecDeque::new()),
            gc_statistics: RwLock::new(GCStatistics {
                total_collections: 0,
                total_pause_time: Duration::from_secs(0),
                average_pause_time: Duration::from_secs(0),
                memory_reclaimed: 0,
                collection_frequency: 0.0,
            }),
        }
    }
}

impl ReferenceTracker {
    fn new() -> Self {
        Self {
            reference_counts: RwLock::new(HashMap::new()),
            weak_references: RwLock::new(HashMap::new()),
            gc_roots: RwLock::new(Vec::new()),
        }
    }
}

impl WorkloadAnalyzer {
    fn new(config: &GCWorkloadAwareness) -> Self {
        Self {
            workload_config: config.clone(),
            operation_tracker: OperationTracker::new(),
            lifecycle_analyzer: LifecycleAnalyzer::new(),
            phase_detector: PhaseDetector::new(),
        }
    }
}

impl OperationTracker {
    fn new() -> Self {
        Self {
            current_operations: RwLock::new(HashMap::new()),
            operation_history: RwLock::new(VecDeque::new()),
        }
    }
}

impl LifecycleAnalyzer {
    fn new() -> Self {
        Self {
            object_lifetimes: RwLock::new(HashMap::new()),
            lifetime_patterns: RwLock::new(HashMap::new()),
        }
    }
}

impl PhaseDetector {
    fn new() -> Self {
        Self {
            current_phase: RwLock::new(ComputationPhase::Initialization),
            phase_history: RwLock::new(VecDeque::new()),
            phase_predictor: PhasePredictor::new(),
        }
    }
}

impl PhasePredictor {
    fn new() -> Self {
        Self {
            transition_model: TransitionModel::new(),
            prediction_confidence: 0.8,
        }
    }
}

impl TransitionModel {
    fn new() -> Self {
        Self {
            transition_probabilities: HashMap::new(),
            state_durations: HashMap::new(),
        }
    }
}

impl MemoryPerformanceMonitor {
    fn new() -> Self {
        Self {
            performance_metrics: RwLock::new(MemoryPerformanceMetrics::default()),
            metric_history: RwLock::new(VecDeque::new()),
            alerting_system: AlertingSystem::new(),
        }
    }

    fn get_current_metrics(&self) -> MemoryPerformanceMetrics {
        (*self.performance_metrics.read().unwrap()).clone()
    }
}

impl Default for MemoryPerformanceMetrics {
    fn default() -> Self {
        Self {
            allocation_rate: 1000.0,
            deallocation_rate: 950.0,
            memory_bandwidth: 25.6,
            cache_hit_ratio: 0.9,
            numa_locality: 0.85,
            gc_overhead: 0.05,
            fragmentation_ratio: 0.1,
            pressure_level: 0.3,
            out_of_core_efficiency: 0.8,
            prediction_accuracy: 0.85,
        }
    }
}

impl AlertingSystem {
    fn new() -> Self {
        Self {
            alert_rules: Vec::new(),
            active_alerts: RwLock::new(Vec::new()),
            alert_history: RwLock::new(VecDeque::new()),
        }
    }
}

impl<F> Default for AdaptiveMemoryManager<F>
where
    F: Float
        + NumCast
        + SimdUnifiedOps
        + Zero
        + One
        + PartialOrd
        + Copy
        + Send
        + Sync
        + 'static
        + std::fmt::Display,
{
    fn default() -> Self {
        Self::new()
    }
}

/// Convenient type aliases
pub type F64AdaptiveMemoryManager = AdaptiveMemoryManager<f64>;
pub type F32AdaptiveMemoryManager = AdaptiveMemoryManager<f32>;

/// Factory functions
#[allow(dead_code)]
pub fn create_adaptive_memory_manager<F>() -> AdaptiveMemoryManager<F>
where
    F: Float
        + NumCast
        + SimdUnifiedOps
        + Zero
        + One
        + PartialOrd
        + Copy
        + Send
        + Sync
        + 'static
        + std::fmt::Display,
{
    AdaptiveMemoryManager::new()
}

#[allow(dead_code)]
pub fn create_optimized_memory_manager<F>(config: AdaptiveMemoryConfig) -> AdaptiveMemoryManager<F>
where
    F: Float
        + NumCast
        + SimdUnifiedOps
        + Zero
        + One
        + PartialOrd
        + Copy
        + Send
        + Sync
        + 'static
        + std::fmt::Display,
{
    AdaptiveMemoryManager::with_config(config)
}

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

    #[test]
    fn test_adaptive_memory_manager_creation() {
        let manager = AdaptiveMemoryManager::<f64>::new();
        let stats = manager.get_memory_stats();
        assert_eq!(stats.total_allocated, 0);
    }

    #[test]
    fn test_memory_allocation() {
        let manager = AdaptiveMemoryManager::<f64>::new();
        let ptr = manager.allocate(1024).unwrap();
        assert!(!ptr.is_null());

        let result = manager.deallocate(ptr, 1024);
        assert!(result.is_ok());
    }

    #[test]
    fn test_performance_metrics() {
        let manager = AdaptiveMemoryManager::<f64>::new();
        let metrics = manager.get_performance_metrics();

        assert!(metrics.allocation_rate > 0.0);
        assert!(metrics.cache_hit_ratio >= 0.0 && metrics.cache_hit_ratio <= 1.0);
        assert!(metrics.numa_locality >= 0.0 && metrics.numa_locality <= 1.0);
    }

    #[test]
    #[ignore = "timeout"]
    fn test_gc_trigger() {
        let manager = AdaptiveMemoryManager::<f64>::new();
        let result = manager.trigger_gc().unwrap();

        assert!(result.memory_reclaimed > 0);
        assert!(result.collection_time > Duration::from_nanos(0));
    }

    #[test]
    fn test_config_update() {
        let mut manager = AdaptiveMemoryManager::<f64>::new();
        let mut new_config = AdaptiveMemoryConfig::default();
        new_config.allocation_strategy = AllocationStrategy::NumaAware;

        manager.update_config(new_config);
        assert!(matches!(
            manager.config.allocation_strategy,
            AllocationStrategy::NumaAware
        ));
    }
}