torsh-backend 0.1.2

//! CUDA unified memory management
//!
//! This module provides comprehensive unified memory management including
//! automatic data migration, prefetching optimization, and memory advice
//! for optimal performance across host and device execution.

// Allow unused variables for unified memory stubs
#![allow(unused_variables)]

use super::allocation::{
    AccessFrequency, AllocationRequest, AllocationStats, AllocationType, DataLocality,
    MigrationStats, UnifiedAllocation,
};
use crate::cuda::cuda_sys_compat as cuda_sys;
use crate::cuda::error::{CudaError, CudaResult};
use std::collections::HashMap;
use std::sync::{
    atomic::{AtomicUsize, Ordering},
    Arc, Mutex,
};
use std::time::{Duration, Instant};

/// CUDA unified memory manager with automatic optimization
///
/// Manages unified memory allocations that can be accessed from both
/// host and device with automatic data migration and performance optimization.
#[derive(Debug)]
pub struct UnifiedMemoryManager {
    /// Unified memory allocations tracking
    allocations: Mutex<HashMap<usize, UnifiedAllocation>>,

    /// Total allocated unified memory
    total_allocated: AtomicUsize,

    /// Peak unified memory usage
    peak_allocated: AtomicUsize,

    /// Configuration settings
    config: UnifiedMemoryConfig,

    /// Performance statistics
    stats: Mutex<UnifiedMemoryStats>,

    /// Migration tracking and optimization
    migration_tracker: Arc<Mutex<MigrationTracker>>,

    /// Prefetch scheduler for optimization
    prefetch_scheduler: Arc<Mutex<PrefetchScheduler>>,

    /// Memory advice manager
    advice_manager: AdviceManager,
}

/// Configuration for unified memory management
#[derive(Debug, Clone)]
pub struct UnifiedMemoryConfig {
    /// Enable automatic prefetching
    pub enable_auto_prefetch: bool,

    /// Enable migration tracking
    pub enable_migration_tracking: bool,

    /// Enable adaptive memory advice
    pub enable_adaptive_advice: bool,

    /// Prefetch threshold for automatic prefetching
    pub prefetch_threshold: usize,

    /// Migration cost threshold
    pub migration_cost_threshold: f64,

    /// Enable concurrent access optimization
    pub enable_concurrent_access: bool,

    /// Memory advice update interval
    pub advice_update_interval: Duration,

    /// Enable performance profiling
    pub enable_profiling: bool,
}

/// Unified memory statistics
#[derive(Debug, Clone)]
pub struct UnifiedMemoryStats {
    /// Base allocation statistics
    pub allocation_stats: AllocationStats,

    /// Migration statistics
    pub migration_stats: MigrationStats,

    /// Prefetch statistics
    pub prefetch_stats: PrefetchStats,

    /// Memory advice effectiveness
    pub advice_effectiveness: f32,

    /// Performance improvement from optimizations
    pub performance_improvement: f32,

    /// Total page faults
    pub page_faults: u64,

    /// Average access latency
    pub average_access_latency: Duration,
}

/// Prefetch operation statistics
#[derive(Debug, Clone)]
pub struct PrefetchStats {
    /// Total prefetch operations
    pub total_prefetches: u64,

    /// Successful prefetches (reduced page faults)
    pub successful_prefetches: u64,

    /// Total bytes prefetched
    pub total_bytes_prefetched: u64,

    /// Average prefetch time
    pub average_prefetch_time: Duration,

    /// Prefetch accuracy (useful vs total)
    pub prefetch_accuracy: f32,
}

/// Migration tracking and prediction
#[derive(Debug)]
pub struct MigrationTracker {
    /// Migration history for pattern analysis
    migration_history: Vec<MigrationEvent>,

    /// Access pattern analysis
    access_patterns: HashMap<usize, AccessPattern>,

    /// Migration prediction model
    prediction_model: MigrationPredictor,

    /// Performance metrics
    migration_metrics: MigrationMetrics,
}

/// Individual migration event
#[derive(Debug, Clone)]
pub struct MigrationEvent {
    /// Memory pointer address
    pub ptr_addr: usize,

    /// Size of migrated data
    pub size: usize,

    /// Source location (device ID or host)
    pub from_location: Location,

    /// Destination location
    pub to_location: Location,

    /// Migration timestamp
    pub timestamp: Instant,

    /// Migration duration
    pub duration: Duration,

    /// Reason for migration
    pub reason: MigrationReason,
}

/// Memory access pattern analysis
#[derive(Debug, Clone)]
pub struct AccessPattern {
    /// Recent access history
    pub access_history: Vec<AccessEvent>,

    /// Dominant access location
    pub dominant_location: Location,

    /// Access frequency pattern
    pub frequency_pattern: AccessFrequency,

    /// Data locality characteristics
    pub locality: DataLocality,

    /// Predicted next access
    pub next_access_prediction: Option<Location>,

    /// Pattern confidence score
    pub confidence: f32,
}

/// Memory access event
#[derive(Debug, Clone)]
pub struct AccessEvent {
    /// Access location
    pub location: Location,

    /// Access timestamp
    pub timestamp: Instant,

    /// Access type (read/write)
    pub access_type: AccessType,

    /// Access size
    pub size: usize,
}

/// Access types for tracking
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum AccessType {
    Read,
    Write,
    ReadWrite,
}

/// Memory locations
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum Location {
    Host,
    Device(usize),
}

/// Reasons for memory migration
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum MigrationReason {
    /// Page fault triggered migration
    PageFault,
    /// Prefetch operation
    Prefetch,
    /// Manual prefetch request
    ManualPrefetch,
    /// Memory advice optimization
    AdviceOptimization,
    /// Automatic optimization
    AutoOptimization,
}

/// Migration prediction model
#[derive(Debug)]
pub struct MigrationPredictor {
    /// Pattern recognition weights
    pattern_weights: HashMap<String, f32>,

    /// Migration cost model
    cost_model: CostModel,

    /// Prediction accuracy history
    accuracy_history: Vec<f32>,

    /// Learning rate for model updates
    learning_rate: f32,
}

/// Migration cost modeling
#[derive(Debug, Clone)]
pub struct CostModel {
    /// Base migration cost per byte
    pub base_cost_per_byte: f64,

    /// Setup cost for migration
    pub setup_cost: f64,

    /// Bandwidth estimates
    pub host_to_device_bandwidth: f64,

    /// Device to host bandwidth
    pub device_to_host_bandwidth: f64,

    /// Latency estimates
    pub migration_latency: Duration,
}

/// Migration performance metrics
#[derive(Debug, Clone)]
pub struct MigrationMetrics {
    /// Total migration time
    pub total_migration_time: Duration,

    /// Migration efficiency (bytes/second)
    pub migration_efficiency: f64,

    /// Avoided migrations through prediction
    pub avoided_migrations: u64,

    /// Cost savings from optimization
    pub cost_savings: f64,
}

/// Prefetch scheduler for optimization
#[derive(Debug)]
pub struct PrefetchScheduler {
    /// Scheduled prefetch operations
    scheduled_operations: Vec<PrefetchOperation>,

    /// Active prefetch tasks
    active_tasks: HashMap<usize, PrefetchTask>,

    /// Prefetch history for learning
    prefetch_history: Vec<PrefetchOutcome>,

    /// Scheduling strategy
    strategy: PrefetchStrategy,
}

/// Prefetch operation definition
#[derive(Debug, Clone)]
pub struct PrefetchOperation {
    /// Memory pointer address to prefetch
    pub ptr_addr: usize,

    /// Size to prefetch
    pub size: usize,

    /// Target location
    pub target_location: Location,

    /// Scheduled execution time
    pub scheduled_time: Instant,

    /// Priority level
    pub priority: PrefetchPriority,

    /// Prediction confidence
    pub confidence: f32,
}

/// Active prefetch task
#[derive(Debug)]
pub struct PrefetchTask {
    /// Operation details
    pub operation: PrefetchOperation,

    /// Task start time
    pub start_time: Instant,

    /// Expected completion time
    pub expected_completion: Instant,

    /// Current status
    pub status: TaskStatus,
}

/// Prefetch operation outcome
#[derive(Debug, Clone)]
pub struct PrefetchOutcome {
    /// Original operation
    pub operation: PrefetchOperation,

    /// Actual execution time
    pub execution_time: Duration,

    /// Whether prefetch was beneficial
    pub was_beneficial: bool,

    /// Performance improvement
    pub improvement: f64,
}

/// Prefetch scheduling strategies
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum PrefetchStrategy {
    /// Immediate prefetch on prediction
    Immediate,
    /// Batched prefetch operations
    Batched,
    /// Adaptive based on system load
    Adaptive,
    /// Conservative (high confidence only)
    Conservative,
}

/// Prefetch operation priorities
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
pub enum PrefetchPriority {
    Low,
    Medium,
    High,
    Critical,
}

/// Task execution status
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum TaskStatus {
    Scheduled,
    Running,
    Completed,
    Failed,
    Cancelled,
}

/// Memory advice manager for optimization
#[derive(Debug)]
pub struct AdviceManager {
    /// Current advice settings per allocation
    advice_settings: Mutex<HashMap<usize, MemoryAdviceSettings>>,

    /// Advice effectiveness tracking
    effectiveness_tracker: EffectivenessTracker,

    /// Advice optimization engine
    optimization_engine: AdviceOptimizer,
}

/// Memory advice settings for an allocation
#[derive(Debug, Clone)]
pub struct MemoryAdviceSettings {
    /// Read-mostly hint
    pub read_mostly: Option<bool>,

    /// Preferred location
    pub preferred_location: Option<Location>,

    /// Accessing devices
    pub accessing_devices: Vec<usize>,

    /// Last update time
    pub last_updated: Instant,

    /// Effectiveness score
    pub effectiveness: f32,
}

/// Memory advice for unified memory optimization
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum MemoryAdvice {
    /// Data will be read-only from GPU
    SetReadMostly,
    /// Unset read-only hint
    UnsetReadMostly,
    /// Set preferred location for data
    SetPreferredLocation,
    /// Unset preferred location
    UnsetPreferredLocation,
    /// Set device that will access data
    SetAccessedBy,
    /// Unset device access hint
    UnsetAccessedBy,
}

/// Effectiveness tracking for memory advice
#[derive(Debug)]
pub struct EffectivenessTracker {
    /// Performance before and after advice
    performance_deltas: Vec<PerformanceDelta>,

    /// Advice impact analysis
    impact_analysis: HashMap<MemoryAdvice, ImpactMetrics>,

    /// Overall effectiveness score
    overall_effectiveness: f32,
}

/// Performance change measurement
#[derive(Debug, Clone)]
pub struct PerformanceDelta {
    /// Memory address (using usize instead of raw pointer for thread safety)
    pub ptr_address: usize,

    /// Applied advice
    pub advice: MemoryAdvice,

    /// Performance before advice
    pub before: PerformanceMetrics,

    /// Performance after advice
    pub after: PerformanceMetrics,

    /// Measurement timestamp
    pub timestamp: Instant,
}

/// Performance metrics for comparison
#[derive(Debug, Clone)]
pub struct PerformanceMetrics {
    /// Access latency
    pub access_latency: Duration,

    /// Migration frequency
    pub migration_frequency: f32,

    /// Page fault rate
    pub page_fault_rate: f32,

    /// Bandwidth utilization
    pub bandwidth_utilization: f32,
}

/// Impact metrics for advice types
#[derive(Debug, Clone)]
pub struct ImpactMetrics {
    /// Average performance improvement
    pub avg_improvement: f32,

    /// Success rate of advice
    pub success_rate: f32,

    /// Confidence in advice effectiveness
    pub confidence: f32,

    /// Number of samples
    pub sample_count: usize,
}

/// Advice optimization engine
#[derive(Debug)]
pub struct AdviceOptimizer {
    /// Optimization rules
    optimization_rules: Vec<OptimizationRule>,

    /// Learning model for advice selection
    learning_model: AdviceLearningModel,

    /// Optimization history
    optimization_history: Vec<OptimizationResult>,
}

/// Optimization rule for automatic advice
#[derive(Debug, Clone)]
pub struct OptimizationRule {
    /// Rule identifier
    pub id: String,

    /// Condition for rule application
    pub condition: String, // Simplified - would be proper predicate

    /// Recommended advice
    pub advice: MemoryAdvice,

    /// Rule confidence
    pub confidence: f32,

    /// Success rate of this rule
    pub success_rate: f32,
}

/// Learning model for advice selection
#[derive(Debug)]
pub struct AdviceLearningModel {
    /// Feature weights for decision making
    feature_weights: HashMap<String, f32>,

    /// Model accuracy
    accuracy: f32,

    /// Training examples
    training_data: Vec<TrainingExample>,
}

/// Training example for learning
#[derive(Debug, Clone)]
pub struct TrainingExample {
    /// Input features
    pub features: HashMap<String, f32>,

    /// Applied advice
    pub advice: MemoryAdvice,

    /// Outcome effectiveness
    pub effectiveness: f32,
}

/// Optimization operation result
#[derive(Debug, Clone)]
pub struct OptimizationResult {
    /// Target allocation pointer address
    pub ptr_addr: usize,

    /// Applied optimization
    pub optimization: String,

    /// Performance improvement
    pub improvement: f32,

    /// Optimization timestamp
    pub timestamp: Instant,
}

impl UnifiedMemoryManager {
    /// Create new unified memory manager
    pub fn new() -> Self {
        Self::new_with_config(UnifiedMemoryConfig::default())
    }

    /// Create unified memory manager with configuration
    pub fn new_with_config(config: UnifiedMemoryConfig) -> Self {
        Self {
            allocations: Mutex::new(HashMap::new()),
            total_allocated: AtomicUsize::new(0),
            peak_allocated: AtomicUsize::new(0),
            config,
            stats: Mutex::new(UnifiedMemoryStats::default()),
            migration_tracker: Arc::new(Mutex::new(MigrationTracker::new())),
            prefetch_scheduler: Arc::new(Mutex::new(PrefetchScheduler::new())),
            advice_manager: AdviceManager::new(),
        }
    }

    /// Allocate unified memory
    pub fn allocate_unified(&self, size: usize) -> CudaResult<UnifiedAllocation> {
        let request = AllocationRequest {
            size,
            allocation_type: AllocationType::Unified,
            ..Default::default()
        };

        self.allocate_unified_with_request(request)
    }

    /// Allocate unified memory with detailed request
    pub fn allocate_unified_with_request(
        &self,
        request: AllocationRequest,
    ) -> CudaResult<UnifiedAllocation> {
        // Allocate unified memory
        let ptr = self.allocate_managed_memory(request.size)?;

        let allocation = UnifiedAllocation::new(ptr, request.size);

        // Track allocation
        {
            let mut allocations = self.allocations.lock().map_err(|_| CudaError::Context {
                message: "Failed to acquire allocations lock".to_string(),
            })?;
            allocations.insert(ptr as usize, allocation.clone());
        }

        // Update statistics
        self.update_allocation_stats(request.size);

        // Initialize migration tracking if enabled
        if self.config.enable_migration_tracking {
            if let Ok(mut tracker) = self.migration_tracker.lock() {
                tracker.initialize_allocation(ptr as usize, request.size);
            }
        }

        // Set initial memory advice if enabled
        if self.config.enable_adaptive_advice {
            let _ = self.apply_initial_advice(ptr, request.size);
        }

        Ok(allocation)
    }

    /// Deallocate unified memory
    pub fn deallocate_unified(&self, allocation: UnifiedAllocation) -> CudaResult<()> {
        let ptr = allocation.ptr;
        let ptr_usize = ptr.as_ptr() as usize;

        // Remove from tracking
        {
            let mut allocations = self.allocations.lock().map_err(|_| CudaError::Context {
                message: "Failed to acquire allocations lock".to_string(),
            })?;
            allocations.remove(&ptr_usize);
        }

        // Clean up migration tracking
        if self.config.enable_migration_tracking {
            if let Ok(mut tracker) = self.migration_tracker.lock() {
                tracker.cleanup_allocation(ptr_usize);
            }
        }

        // Free unified memory
        unsafe {
            let result = cuda_sys::cudaFree(ptr.as_ptr() as *mut std::ffi::c_void);
            if result != crate::cuda::cudaSuccess {
                return Err(CudaError::Context {
                    message: format!("Failed to free unified memory: {:?}", result),
                });
            }
        }

        // Update statistics
        self.update_deallocation_stats(allocation.size);

        Ok(())
    }

    /// Prefetch memory to device
    pub fn prefetch_to_device(
        &self,
        ptr: *mut u8,
        size: usize,
        device_id: Option<usize>,
    ) -> CudaResult<()> {
        let target_device = device_id.unwrap_or(0) as i32;

        unsafe {
            let result = cuda_sys::cudaMemPrefetchAsync(
                ptr as *const std::ffi::c_void,
                size,
                target_device,
                0 as crate::cuda::cudaStream_t,
            );

            if result != crate::cuda::cudaSuccess {
                return Err(CudaError::Context {
                    message: format!("Failed to prefetch memory: {:?}", result),
                });
            }
        }

        // Record prefetch operation
        if self.config.enable_auto_prefetch {
            self.record_prefetch_operation(ptr, size, Location::Device(target_device as usize));
        }

        Ok(())
    }

    /// Prefetch memory to host
    pub fn prefetch_to_host(&self, ptr: *mut u8, size: usize) -> CudaResult<()> {
        unsafe {
            let result = cuda_sys::cudaMemPrefetchAsync(
                ptr as *const std::ffi::c_void,
                size,
                cuda_sys::cudaCpuDeviceId as i32,
                0 as crate::cuda::cudaStream_t,
            );

            if result != crate::cuda::cudaSuccess {
                return Err(CudaError::Context {
                    message: format!("Failed to prefetch memory to host: {:?}", result),
                });
            }
        }

        // Record prefetch operation
        if self.config.enable_auto_prefetch {
            self.record_prefetch_operation(ptr, size, Location::Host);
        }

        Ok(())
    }

    /// Set memory advice for optimization
    pub fn set_memory_advice(
        &self,
        ptr: *mut u8,
        size: usize,
        advice: MemoryAdvice,
        device_id: Option<usize>,
    ) -> CudaResult<()> {
        let device = device_id.unwrap_or(0) as i32;
        let cuda_advice = self.convert_memory_advice(advice);

        unsafe {
            let result =
                cuda_sys::cudaMemAdvise(ptr as *const std::ffi::c_void, size, cuda_advice, device);

            if result != crate::cuda::cudaSuccess {
                return Err(CudaError::Context {
                    message: format!("Failed to set memory advice: {:?}", result),
                });
            }
        }

        // Track advice effectiveness
        if self.config.enable_adaptive_advice {
            self.advice_manager
                .track_advice_application(ptr as usize, advice);
        }

        Ok(())
    }

    /// Get unified memory statistics
    pub fn get_statistics(&self) -> CudaResult<UnifiedMemoryStats> {
        let stats = self.stats.lock().map_err(|_| CudaError::Context {
            message: "Failed to acquire statistics lock".to_string(),
        })?;
        Ok(stats.clone())
    }

    /// Run automatic optimization
    pub fn optimize_allocations(&self) -> CudaResult<OptimizationSummary> {
        let start_time = Instant::now();
        let mut optimizations_applied = 0;
        let mut total_improvement = 0.0;

        // Get current allocations
        let allocations = self.allocations.lock().map_err(|_| CudaError::Context {
            message: "Failed to acquire allocations lock".to_string(),
        })?;

        for (ptr_usize, _allocation) in allocations.iter() {
            // Analyze access patterns
            if let Ok(tracker) = self.migration_tracker.lock() {
                if let Some(pattern) = tracker.access_patterns.get(ptr_usize) {
                    // Apply optimizations based on patterns
                    if let Some(optimization) = self.suggest_optimization(pattern) {
                        if let Ok(improvement) =
                            self.apply_optimization(*ptr_usize as *mut u8, optimization)
                        {
                            optimizations_applied += 1;
                            total_improvement += improvement;
                        }
                    }
                }
            }
        }

        Ok(OptimizationSummary {
            duration: start_time.elapsed(),
            optimizations_applied,
            average_improvement: if optimizations_applied > 0 {
                total_improvement / optimizations_applied as f32
            } else {
                0.0
            },
            total_improvement,
        })
    }

    // Private implementation methods

    fn allocate_managed_memory(&self, size: usize) -> CudaResult<*mut u8> {
        let mut ptr: *mut std::ffi::c_void = std::ptr::null_mut();

        unsafe {
            let result = cuda_sys::cudaMallocManaged(
                &mut ptr as *mut *mut std::ffi::c_void,
                size,
                cuda_sys::cudaMemAttachGlobal,
            );

            if result != crate::cuda::cudaSuccess {
                return Err(CudaError::Context {
                    message: format!("Failed to allocate managed memory: {:?}", result),
                });
            }
        }

        Ok(ptr as *mut u8)
    }

    fn convert_memory_advice(&self, advice: MemoryAdvice) -> cuda_sys::cudaMemoryAdvise {
        match advice {
            MemoryAdvice::SetReadMostly => cuda_sys::cudaMemoryAdvise_cudaMemAdviseSetReadMostly,
            MemoryAdvice::UnsetReadMostly => {
                cuda_sys::cudaMemoryAdvise_cudaMemAdviseUnsetReadMostly
            }
            MemoryAdvice::SetPreferredLocation => {
                cuda_sys::cudaMemoryAdvise_cudaMemAdviseSetPreferredLocation
            }
            MemoryAdvice::UnsetPreferredLocation => {
                cuda_sys::cudaMemoryAdvise_cudaMemAdviseUnsetPreferredLocation
            }
            MemoryAdvice::SetAccessedBy => cuda_sys::cudaMemoryAdvise_cudaMemAdviseSetAccessedBy,
            MemoryAdvice::UnsetAccessedBy => {
                cuda_sys::cudaMemoryAdvise_cudaMemAdviseUnsetAccessedBy
            }
        }
    }

    fn update_allocation_stats(&self, size: usize) {
        let current = self.total_allocated.fetch_add(size, Ordering::Relaxed) + size;

        // Update peak
        let mut peak = self.peak_allocated.load(Ordering::Relaxed);
        while current > peak {
            match self.peak_allocated.compare_exchange_weak(
                peak,
                current,
                Ordering::Relaxed,
                Ordering::Relaxed,
            ) {
                Ok(_) => break,
                Err(new_peak) => peak = new_peak,
            }
        }

        // Update detailed statistics
        if let Ok(mut stats) = self.stats.lock() {
            stats.allocation_stats.total_allocations += 1;
            stats.allocation_stats.active_allocations += 1;
            stats.allocation_stats.total_bytes_allocated += size as u64;
            stats.allocation_stats.current_bytes_allocated = current as u64;
            stats.allocation_stats.peak_bytes_allocated = peak as u64;
        }
    }

    fn update_deallocation_stats(&self, size: usize) {
        self.total_allocated.fetch_sub(size, Ordering::Relaxed);

        if let Ok(mut stats) = self.stats.lock() {
            stats.allocation_stats.active_allocations =
                stats.allocation_stats.active_allocations.saturating_sub(1);
            stats.allocation_stats.current_bytes_allocated =
                self.total_allocated.load(Ordering::Relaxed) as u64;
        }
    }

    fn record_prefetch_operation(&self, ptr: *mut u8, size: usize, target: Location) {
        if let Ok(mut stats) = self.stats.lock() {
            stats.prefetch_stats.total_prefetches += 1;
            stats.prefetch_stats.total_bytes_prefetched += size as u64;
        }
    }

    fn apply_initial_advice(&self, ptr: *mut u8, size: usize) -> CudaResult<()> {
        // Apply conservative initial advice
        self.set_memory_advice(ptr, size, MemoryAdvice::SetReadMostly, None)
    }

    fn suggest_optimization(&self, pattern: &AccessPattern) -> Option<MemoryAdvice> {
        match pattern.dominant_location {
            Location::Host => Some(MemoryAdvice::SetPreferredLocation),
            Location::Device(_) => {
                if pattern.frequency_pattern == AccessFrequency::VeryHigh {
                    Some(MemoryAdvice::SetReadMostly)
                } else {
                    Some(MemoryAdvice::SetPreferredLocation)
                }
            }
        }
    }

    fn apply_optimization(&self, ptr: *mut u8, advice: MemoryAdvice) -> CudaResult<f32> {
        // Apply optimization and measure improvement
        self.set_memory_advice(ptr, 0, advice, None)?;

        // Return simulated improvement
        Ok(0.1) // 10% improvement placeholder
    }
}

/// Optimization summary
#[derive(Debug, Clone)]
pub struct OptimizationSummary {
    /// Optimization duration
    pub duration: Duration,

    /// Number of optimizations applied
    pub optimizations_applied: usize,

    /// Average performance improvement
    pub average_improvement: f32,

    /// Total performance improvement
    pub total_improvement: f32,
}

// Default implementations and constructors
impl Default for UnifiedMemoryConfig {
    fn default() -> Self {
        Self {
            enable_auto_prefetch: true,
            enable_migration_tracking: true,
            enable_adaptive_advice: true,
            prefetch_threshold: 1024 * 1024, // 1MB
            migration_cost_threshold: 0.1,
            enable_concurrent_access: true,
            advice_update_interval: Duration::from_secs(30),
            enable_profiling: true,
        }
    }
}

impl Default for UnifiedMemoryStats {
    fn default() -> Self {
        Self {
            allocation_stats: AllocationStats::default(),
            migration_stats: MigrationStats::default(),
            prefetch_stats: PrefetchStats::default(),
            advice_effectiveness: 0.0,
            performance_improvement: 0.0,
            page_faults: 0,
            average_access_latency: Duration::from_secs(0),
        }
    }
}

impl Default for PrefetchStats {
    fn default() -> Self {
        Self {
            total_prefetches: 0,
            successful_prefetches: 0,
            total_bytes_prefetched: 0,
            average_prefetch_time: Duration::from_secs(0),
            prefetch_accuracy: 0.0,
        }
    }
}

impl MigrationTracker {
    fn new() -> Self {
        Self {
            migration_history: Vec::new(),
            access_patterns: HashMap::new(),
            prediction_model: MigrationPredictor::new(),
            migration_metrics: MigrationMetrics::default(),
        }
    }

    fn initialize_allocation(&mut self, ptr: usize, _size: usize) {
        let pattern = AccessPattern {
            access_history: Vec::new(),
            dominant_location: Location::Host,
            frequency_pattern: AccessFrequency::Medium,
            locality: DataLocality::Mixed,
            next_access_prediction: None,
            confidence: 0.0,
        };

        self.access_patterns.insert(ptr, pattern);
    }

    fn cleanup_allocation(&mut self, ptr: usize) {
        self.access_patterns.remove(&ptr);
    }
}

impl MigrationPredictor {
    fn new() -> Self {
        Self {
            pattern_weights: HashMap::new(),
            cost_model: CostModel::default(),
            accuracy_history: Vec::new(),
            learning_rate: 0.01,
        }
    }
}

impl Default for CostModel {
    fn default() -> Self {
        Self {
            base_cost_per_byte: 1e-6,       // 1 microsecond per byte
            setup_cost: 10e-6,              // 10 microseconds setup
            host_to_device_bandwidth: 10e9, // 10 GB/s
            device_to_host_bandwidth: 8e9,  // 8 GB/s
            migration_latency: Duration::from_micros(50),
        }
    }
}

impl Default for MigrationMetrics {
    fn default() -> Self {
        Self {
            total_migration_time: Duration::from_secs(0),
            migration_efficiency: 0.0,
            avoided_migrations: 0,
            cost_savings: 0.0,
        }
    }
}

impl PrefetchScheduler {
    fn new() -> Self {
        Self {
            scheduled_operations: Vec::new(),
            active_tasks: HashMap::new(),
            prefetch_history: Vec::new(),
            strategy: PrefetchStrategy::Adaptive,
        }
    }
}

impl AdviceManager {
    fn new() -> Self {
        Self {
            advice_settings: Mutex::new(HashMap::new()),
            effectiveness_tracker: EffectivenessTracker::new(),
            optimization_engine: AdviceOptimizer::new(),
        }
    }

    fn track_advice_application(&self, ptr: usize, advice: MemoryAdvice) {
        // Track the effectiveness of applied advice
        if let Ok(mut settings) = self.advice_settings.lock() {
            let setting = settings.entry(ptr).or_insert_with(|| MemoryAdviceSettings {
                read_mostly: None,
                preferred_location: None,
                accessing_devices: Vec::new(),
                last_updated: Instant::now(),
                effectiveness: 0.0,
            });

            setting.last_updated = Instant::now();

            match advice {
                MemoryAdvice::SetReadMostly => setting.read_mostly = Some(true),
                MemoryAdvice::UnsetReadMostly => setting.read_mostly = Some(false),
                MemoryAdvice::SetPreferredLocation => {
                    setting.preferred_location = Some(Location::Device(0));
                }
                _ => {} // Handle other advice types
            }
        }
    }
}

impl EffectivenessTracker {
    fn new() -> Self {
        Self {
            performance_deltas: Vec::new(),
            impact_analysis: HashMap::new(),
            overall_effectiveness: 0.0,
        }
    }
}

impl AdviceOptimizer {
    fn new() -> Self {
        Self {
            optimization_rules: Vec::new(),
            learning_model: AdviceLearningModel::new(),
            optimization_history: Vec::new(),
        }
    }
}

impl AdviceLearningModel {
    fn new() -> Self {
        Self {
            feature_weights: HashMap::new(),
            accuracy: 0.0,
            training_data: Vec::new(),
        }
    }
}

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

    #[test]
    fn test_unified_memory_config() {
        let config = UnifiedMemoryConfig::default();
        assert!(config.enable_auto_prefetch);
        assert!(config.enable_migration_tracking);
        assert!(config.enable_adaptive_advice);
    }

    #[test]
    fn test_memory_advice_conversion() {
        let manager = UnifiedMemoryManager::new();

        let advice = MemoryAdvice::SetReadMostly;
        let cuda_advice = manager.convert_memory_advice(advice);
        assert_eq!(
            cuda_advice,
            cuda_sys::cudaMemoryAdvise_cudaMemAdviseSetReadMostly
        );
    }

    #[test]
    fn test_migration_tracker() {
        let tracker = MigrationTracker::new();
        assert!(tracker.migration_history.is_empty());
        assert!(tracker.access_patterns.is_empty());
    }

    #[test]
    fn test_prefetch_scheduler() {
        let scheduler = PrefetchScheduler::new();
        assert!(scheduler.scheduled_operations.is_empty());
        assert_eq!(scheduler.strategy, PrefetchStrategy::Adaptive);
    }

    #[test]
    fn test_cost_model() {
        let model = CostModel::default();
        assert!(model.base_cost_per_byte > 0.0);
        assert!(model.setup_cost > 0.0);
        assert!(model.host_to_device_bandwidth > 0.0);
    }

    #[test]
    fn test_access_pattern() {
        let pattern = AccessPattern {
            access_history: Vec::new(),
            dominant_location: Location::Host,
            frequency_pattern: AccessFrequency::High,
            locality: DataLocality::Sequential,
            next_access_prediction: Some(Location::Device(0)),
            confidence: 0.8,
        };

        assert_eq!(pattern.dominant_location, Location::Host);
        assert_eq!(pattern.frequency_pattern, AccessFrequency::High);
        assert_eq!(pattern.confidence, 0.8);
    }
}

// Type aliases and missing types for compatibility

/// Migration strategy for unified memory
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum MigrationStrategy {
    /// Automatic migration based on usage
    Automatic,
    /// Manual migration controlled by application
    Manual,
    /// Lazy migration on first access
    OnDemand,
    /// Eager migration based on predictions
    Predictive,
}

impl Default for MigrationStrategy {
    fn default() -> Self {
        Self::Automatic
    }
}

/// Unified memory metrics
pub type UnifiedMemoryMetrics = UnifiedMemoryStats;

/// Unified memory pool (placeholder for pool implementation)
#[derive(Debug)]
pub struct UnifiedMemoryPool {
    /// Total capacity of the pool
    pub capacity: usize,
    /// Current usage
    pub used: usize,
    /// Pool configuration
    pub config: UnifiedMemoryConfig,
}

impl UnifiedMemoryPool {
    /// Create a new unified memory pool
    pub fn new(capacity: usize, config: UnifiedMemoryConfig) -> Self {
        Self {
            capacity,
            used: 0,
            config,
        }
    }
}