scirs2-integrate 0.4.2

//! Advanced-advanced memory optimization system for ODE solvers
//!
//! This module provides cutting-edge memory management optimizations including:
//! - Predictive memory allocation based on problem characteristics
//! - Multi-level memory hierarchy optimization (L1/L2/L3 cache, RAM, GPU)
//! - Adaptive memory layout reorganization for maximum cache efficiency
//! - Real-time memory usage monitoring and optimization
//! - Zero-copy buffer management and memory-mapped operations
//! - NUMA-aware memory allocation for multi-socket systems

#![allow(dead_code)]
#![allow(clippy::too_many_arguments)]

use crate::common::IntegrateFloat;
use crate::error::IntegrateResult;
use scirs2_core::ndarray::Array2;
use std::collections::{HashMap, VecDeque};
use std::marker::PhantomData;
use std::sync::{Arc, Mutex, RwLock};
use std::time::{Duration, Instant};

/// Advanced-advanced memory optimization manager
pub struct AdvancedMemoryOptimizer<F: IntegrateFloat> {
    /// Multi-level memory hierarchy manager
    hierarchy_manager: Arc<RwLock<MemoryHierarchyManager<F>>>,
    /// Predictive allocation engine
    predictor: Arc<Mutex<AllocationPredictor<F>>>,
    /// Cache optimization system
    cache_optimizer: Arc<Mutex<CacheOptimizer<F>>>,
    /// Real-time memory monitor
    memory_monitor: Arc<Mutex<RealTimeMemoryMonitor>>,
    /// NUMA topology manager
    numa_manager: Arc<RwLock<NumaTopologyManager>>,
    /// Zero-copy buffer pool
    zero_copy_pool: Arc<Mutex<ZeroCopyBufferPool<F>>>,
}

/// Multi-level memory hierarchy management
pub struct MemoryHierarchyManager<F: IntegrateFloat> {
    /// L1 cache-optimized buffers
    l1_buffers: HashMap<String, L1CacheBuffer<F>>,
    /// L2 cache-optimized buffers
    l2_buffers: HashMap<String, L2CacheBuffer<F>>,
    /// L3 cache-optimized buffers
    l3_buffers: HashMap<String, L3CacheBuffer<F>>,
    /// Main memory buffers
    ram_buffers: HashMap<String, RamBuffer<F>>,
    /// GPU memory buffers
    gpu_buffers: HashMap<String, GpuBuffer<F>>,
    /// Memory usage statistics
    usage_stats: MemoryUsageStatistics,
    /// Cache hierarchy information
    cache_info: CacheHierarchyInfo,
}

/// L1 cache-optimized buffer (typically 32KB per core)
#[derive(Debug, Clone)]
pub struct L1CacheBuffer<F: IntegrateFloat> {
    /// Buffer identifier
    id: String,
    /// Data storage aligned for L1 cache lines
    data: Vec<F>,
    /// Cache line size (typically 64 bytes)
    cache_line_size: usize,
    /// Access pattern for optimization
    access_pattern: AccessPattern,
    /// Last access timestamp
    last_access: Instant,
    /// Access frequency counter
    access_count: usize,
}

/// L2 cache-optimized buffer (typically 256KB-1MB per core)
#[derive(Debug, Clone)]
pub struct L2CacheBuffer<F: IntegrateFloat> {
    /// Buffer identifier
    id: String,
    /// Data storage optimized for L2 cache
    data: Vec<F>,
    /// Prefetch strategy
    prefetch_strategy: PrefetchStrategy,
    /// Memory layout optimization
    layout: MemoryLayout,
    /// Usage statistics
    usage_stats: BufferUsageStats,
}

/// L3 cache-optimized buffer (typically 8-32MB shared)
#[derive(Debug, Clone)]
pub struct L3CacheBuffer<F: IntegrateFloat> {
    /// Buffer identifier
    id: String,
    /// Data storage optimized for L3 cache
    data: Vec<F>,
    /// Sharing strategy across cores
    sharing_strategy: SharingStrategy,
    /// Cache replacement policy
    replacement_policy: ReplacementPolicy,
    /// Performance metrics
    performance_metrics: CachePerformanceMetrics,
}

/// Main memory buffer with NUMA optimization
#[derive(Debug, Clone)]
pub struct RamBuffer<F: IntegrateFloat> {
    /// Buffer identifier
    id: String,
    /// Data storage with NUMA placement
    data: Vec<F>,
    /// NUMA node assignment
    numa_node: usize,
    /// Memory bandwidth utilization
    bandwidth_usage: f64,
    /// Large page allocation
    use_large_pages: bool,
}

/// GPU memory buffer for heterogeneous computing
#[derive(Debug, Clone)]
pub struct GpuBuffer<F: IntegrateFloat> {
    /// Buffer identifier
    id: String,
    /// GPU device assignment
    device_id: usize,
    /// Phantom data for type parameter
    _phantom: PhantomData<F>,
    /// Memory type (global, shared, constant, texture)
    memory_type: GpuMemoryType,
    /// Size in elements
    size: usize,
    /// Coherency state with CPU memory
    coherency_state: CoherencyState,
}

/// Memory access patterns for optimization
#[derive(Debug, Clone, PartialEq)]
pub enum AccessPattern {
    /// Sequential access (optimal for prefetching)
    Sequential,
    /// Random access (needs different optimization)
    Random,
    /// Strided access (common in matrix operations)
    Strided { stride: usize },
    /// Blocked access (common in tiled algorithms)
    Blocked { block_size: usize },
    /// Temporal locality (repeated access to same data)
    Temporal,
}

/// Memory prefetch strategies
#[derive(Debug, Clone)]
pub enum PrefetchStrategy {
    /// No prefetching
    None,
    /// Software prefetch with fixed distance
    Software { distance: usize },
    /// Hardware prefetch hints
    Hardware,
    /// Adaptive prefetch based on access pattern
    Adaptive,
}

/// Memory layout optimization strategies
#[derive(Debug, Clone)]
pub enum MemoryLayout {
    /// Array of Structures
    AoS,
    /// Structure of Arrays
    SoA,
    /// Hybrid layout
    Hybrid,
    /// Cache-blocked layout
    CacheBlocked { block_size: usize },
}

/// Cache sharing strategies for L3
#[derive(Debug, Clone)]
pub enum SharingStrategy {
    /// Exclusive access by single core
    Exclusive,
    /// Shared read-only across cores
    SharedReadOnly,
    /// Shared read-write with coherency
    SharedReadWrite,
    /// Partitioned among cores
    Partitioned,
}

/// Cache replacement policies
#[derive(Debug, Clone)]
pub enum ReplacementPolicy {
    /// Least Recently Used
    LRU,
    /// Least Frequently Used
    LFU,
    /// First In First Out
    FIFO,
    /// Random replacement
    Random,
    /// Adaptive replacement based on workload
    Adaptive,
}

/// GPU memory types
#[derive(Debug, Clone)]
pub enum GpuMemoryType {
    /// Global memory (largest, slowest)
    Global,
    /// Shared memory (fast, limited size)
    Shared,
    /// Constant memory (cached, read-only)
    Constant,
    /// Texture memory (cached, optimized for spatial locality)
    Texture,
    /// Register memory (fastest, very limited)
    Register,
}

/// Memory coherency states
#[derive(Debug, Clone)]
pub enum CoherencyState {
    /// Data is synchronized between CPU and GPU
    Coherent,
    /// GPU has more recent data
    GpuModified,
    /// CPU has more recent data
    CpuModified,
    /// Data is invalid and needs refresh
    Invalid,
}

/// Predictive memory allocation engine
pub struct AllocationPredictor<F: IntegrateFloat> {
    /// Historical allocation patterns
    allocation_history: VecDeque<AllocationEvent<F>>,
    /// Problem characteristic analyzer
    problem_analyzer: ProblemCharacteristicAnalyzer,
    /// Allocation pattern models
    pattern_models: HashMap<String, AllocationPattern>,
    /// Prediction accuracy tracker
    accuracy_tracker: PredictionAccuracyTracker,
}

/// Memory allocation event for learning
#[derive(Debug, Clone)]
pub struct AllocationEvent<F: IntegrateFloat> {
    /// Timestamp of allocation
    timestamp: Instant,
    /// Problem size and characteristics
    problem_size: usize,
    /// Requested memory size
    memory_size: usize,
    /// Memory type requested
    memory_type: MemoryType,
    /// Access pattern observed
    observed_pattern: AccessPattern,
    /// Performance impact
    performance_impact: PerformanceImpact<F>,
}

/// Memory type classification
#[derive(Debug, Clone, PartialEq)]
pub enum MemoryType {
    /// Solution vectors
    Solution,
    /// Derivative vectors
    Derivative,
    /// Jacobian matrices
    Jacobian,
    /// Temporary workspace
    Workspace,
    /// Constants and parameters
    Constants,
}

/// Performance impact measurement
#[derive(Debug, Clone)]
pub struct PerformanceImpact<F: IntegrateFloat> {
    /// Cache miss rate
    cache_miss_rate: f64,
    /// Memory bandwidth utilization
    bandwidth_utilization: f64,
    /// Execution time impact
    execution_time: Duration,
    /// Energy consumption impact
    energy_consumption: F,
}

/// Problem characteristic analysis for prediction
pub struct ProblemCharacteristicAnalyzer {
    /// System dimension analyzer
    dimension_analyzer: DimensionAnalyzer,
    /// Sparsity pattern analyzer
    sparsity_analyzer: SparsityAnalyzer,
    /// Temporal pattern analyzer
    temporal_analyzer: TemporalAnalyzer,
    /// Stiffness characteristic analyzer
    stiffness_analyzer: StiffnessAnalyzer,
}

/// Cache optimization system
pub struct CacheOptimizer<F: IntegrateFloat> {
    /// Cache-aware algorithm selector
    algorithm_selector: CacheAwareAlgorithmSelector,
    /// Data layout optimizer
    layout_optimizer: DataLayoutOptimizer<F>,
    /// Cache blocking strategy manager
    blocking_manager: CacheBlockingManager,
    /// Prefetch pattern optimizer
    prefetch_optimizer: PrefetchPatternOptimizer,
}

/// Real-time memory monitoring system
pub struct RealTimeMemoryMonitor {
    /// Memory usage tracking
    usage_tracker: MemoryUsageTracker,
    /// Performance counter integration
    perf_counters: PerformanceCounters,
    /// Memory leak detector
    leak_detector: MemoryLeakDetector,
    /// Fragmentation analyzer
    fragmentation_analyzer: FragmentationAnalyzer,
}

/// NUMA topology management
pub struct NumaTopologyManager {
    /// NUMA node topology
    topology: NumaTopology,
    /// Memory placement policies
    placement_policies: HashMap<String, MemoryPlacementPolicy>,
    /// Bandwidth measurements between nodes
    node_bandwidths: Array2<f64>,
    /// CPU affinity management
    cpu_affinity: CpuAffinityManager,
}

/// Zero-copy buffer pool for efficient data transfer
pub struct ZeroCopyBufferPool<F: IntegrateFloat> {
    /// Available zero-copy buffers
    available_buffers: Vec<ZeroCopyBuffer<F>>,
    /// Currently allocated buffers
    allocated_buffers: HashMap<usize, ZeroCopyBuffer<F>>,
    /// Memory-mapped file buffers
    mmap_buffers: Vec<MmapBuffer<F>>,
    /// Buffer reuse statistics
    reuse_stats: BufferReuseStatistics,
}

/// Zero-copy buffer implementation
#[derive(Debug, Clone)]
pub struct ZeroCopyBuffer<F: IntegrateFloat> {
    /// Unique buffer identifier
    id: usize,
    /// Pointer to memory region
    ptr: *mut F,
    /// Buffer size in elements
    size: usize,
    /// Page alignment for zero-copy operations
    page_aligned: bool,
    /// DMA capability
    dma_capable: bool,
}

/// Memory-mapped buffer for large datasets
#[derive(Debug, Clone)]
pub struct MmapBuffer<F: IntegrateFloat> {
    /// Buffer identifier
    id: usize,
    /// Phantom data for type parameter
    _phantom: PhantomData<F>,
    /// File descriptor for memory mapping
    file_descriptor: i32,
    /// Mapped size
    size: usize,
    /// Access mode (read-only, read-write)
    access_mode: AccessMode,
    /// Prefault pages on allocation
    prefault: bool,
}

/// Memory access modes for mmap
#[derive(Debug, Clone)]
pub enum AccessMode {
    ReadOnly,
    ReadWrite,
    WriteOnly,
    CopyOnWrite,
}

impl<F: IntegrateFloat> AdvancedMemoryOptimizer<F> {
    /// Create a new advanced-memory optimizer
    pub fn new() -> IntegrateResult<Self> {
        let hierarchy_manager = Arc::new(RwLock::new(MemoryHierarchyManager::new()?));
        let predictor = Arc::new(Mutex::new(AllocationPredictor::new()));
        let cache_optimizer = Arc::new(Mutex::new(CacheOptimizer::new()?));
        let memory_monitor = Arc::new(Mutex::new(RealTimeMemoryMonitor::new()?));
        let numa_manager = Arc::new(RwLock::new(NumaTopologyManager::new()?));
        let zero_copy_pool = Arc::new(Mutex::new(ZeroCopyBufferPool::new()?));

        Ok(AdvancedMemoryOptimizer {
            hierarchy_manager,
            predictor,
            cache_optimizer,
            memory_monitor,
            numa_manager,
            zero_copy_pool,
        })
    }

    /// Optimize memory allocation for ODE problem
    pub fn optimize_for_problem(
        &self,
        problem_size: usize,
        method_type: &str,
        expected_iterations: usize,
    ) -> IntegrateResult<OptimizationPlan<F>> {
        // Analyze problem characteristics
        let characteristics = self.analyze_problem_characteristics(problem_size, method_type)?;

        // Predict memory requirements
        let memory_requirements = self.predict_memory_requirements(&characteristics)?;

        // Generate optimization plan
        let plan = self.generate_optimization_plan(memory_requirements, expected_iterations)?;

        // Apply cache optimizations
        self.apply_cache_optimizations(&plan)?;

        Ok(plan)
    }

    /// Allocate advanced-optimized memory for solution vectors
    pub fn allocate_solution_memory(
        &self,
        size: usize,
    ) -> IntegrateResult<OptimizedMemoryRegion<F>> {
        // Check predictor for optimal allocation strategy
        let predictor = self.predictor.lock().expect("Operation failed");
        let allocation_strategy =
            predictor.predict_optimal_allocation(size, MemoryType::Solution)?;
        drop(predictor);

        // Allocate based on predicted strategy
        match allocation_strategy.memory_tier {
            MemoryTier::L1Cache => self.allocate_l1_optimized(size, allocation_strategy),
            MemoryTier::L2Cache => self.allocate_l2_optimized(size, allocation_strategy),
            MemoryTier::L3Cache => self.allocate_l3_optimized(size, allocation_strategy),
            MemoryTier::MainMemory => self.allocate_numa_optimized(size, allocation_strategy),
            MemoryTier::GpuMemory => self.allocate_gpu_optimized(size, allocation_strategy),
        }
    }

    /// Analyze problem characteristics for optimization
    fn analyze_problem_characteristics(
        &self,
        problem_size: usize,
        method_type: &str,
    ) -> IntegrateResult<ProblemCharacteristics> {
        Ok(ProblemCharacteristics {
            dimension: problem_size,
            estimated_memory_footprint: problem_size * std::mem::size_of::<F>() * 10, // Estimate
            access_pattern: self.infer_access_pattern(method_type)?,
            computational_intensity: self.estimate_computational_intensity(method_type)?,
            data_locality: self.analyze_data_locality(problem_size)?,
            parallelism_potential: self.assess_parallelism(method_type)?,
        })
    }

    /// Predict memory requirements based on problem characteristics
    fn predict_memory_requirements(
        &self,
        characteristics: &ProblemCharacteristics,
    ) -> IntegrateResult<MemoryRequirements<F>> {
        let predictor = self.predictor.lock().expect("Operation failed");
        predictor.predict_requirements(characteristics)
    }

    /// Generate comprehensive optimization plan
    fn generate_optimization_plan(
        &self,
        requirements: MemoryRequirements<F>,
        expected_iterations: usize,
    ) -> IntegrateResult<OptimizationPlan<F>> {
        Ok(OptimizationPlan {
            memory_layout: self.design_optimal_layout(&requirements)?,
            cache_strategy: self.design_cache_strategy(&requirements)?,
            numa_placement: self.design_numa_placement(&requirements)?,
            prefetch_schedule: self.design_prefetch_schedule(&requirements, expected_iterations)?,
            buffer_reuse_plan: self.design_buffer_reuse(&requirements)?,
            optimization_applied: vec!["Comprehensive optimization".to_string()],
            _phantom: PhantomData,
        })
    }

    /// Apply cache optimizations based on plan
    fn apply_cache_optimizations(&self, plan: &OptimizationPlan<F>) -> IntegrateResult<()> {
        let cache_optimizer = self.cache_optimizer.lock().expect("Operation failed");
        CacheOptimizer::apply_optimizations(plan)
    }

    /// Allocate L1 cache-optimized memory
    fn allocate_l1_optimized(
        &self,
        size: usize,
        strategy: AllocationStrategy,
    ) -> IntegrateResult<OptimizedMemoryRegion<F>> {
        let mut hierarchy = self.hierarchy_manager.write().expect("Operation failed");

        let buffer = L1CacheBuffer {
            id: format!(
                "l1_buffer_{}",
                std::time::SystemTime::now()
                    .duration_since(std::time::UNIX_EPOCH)
                    .expect("Failed to create array")
                    .as_nanos()
            ),
            data: vec![F::zero(); size],
            cache_line_size: 64, // Typical cache line size
            access_pattern: strategy.access_pattern,
            last_access: Instant::now(),
            access_count: 0,
        };

        hierarchy
            .l1_buffers
            .insert(buffer.id.clone(), buffer.clone());

        Ok(OptimizedMemoryRegion {
            id: buffer.id,
            memory_tier: MemoryTier::L1Cache,
            size,
            alignment: 64,
            optimization_applied: vec![
                "L1CacheOptimized".to_string(),
                "CacheLineAligned".to_string(),
            ],
            _phantom: PhantomData,
        })
    }

    /// Allocate L2 cache-optimized memory
    fn allocate_l2_optimized(
        &self,
        size: usize,
        strategy: AllocationStrategy,
    ) -> IntegrateResult<OptimizedMemoryRegion<F>> {
        let mut hierarchy = self.hierarchy_manager.write().expect("Operation failed");

        let buffer = L2CacheBuffer {
            id: format!(
                "l2_buffer_{}",
                std::time::SystemTime::now()
                    .duration_since(std::time::UNIX_EPOCH)
                    .expect("Failed to create array")
                    .as_nanos()
            ),
            data: vec![F::zero(); size],
            prefetch_strategy: strategy.prefetch_strategy,
            layout: strategy.memory_layout,
            usage_stats: BufferUsageStats::new(),
        };

        hierarchy
            .l2_buffers
            .insert(buffer.id.clone(), buffer.clone());

        Ok(OptimizedMemoryRegion {
            id: buffer.id,
            memory_tier: MemoryTier::L2Cache,
            size,
            alignment: 64,
            optimization_applied: vec![
                "L2CacheOptimized".to_string(),
                "PrefetchOptimized".to_string(),
            ],
            _phantom: PhantomData,
        })
    }

    /// Allocate L3 cache-optimized memory
    fn allocate_l3_optimized(
        &self,
        size: usize,
        strategy: AllocationStrategy,
    ) -> IntegrateResult<OptimizedMemoryRegion<F>> {
        let mut hierarchy = self.hierarchy_manager.write().expect("Operation failed");

        let buffer = L3CacheBuffer {
            id: format!(
                "l3_buffer_{}",
                std::time::SystemTime::now()
                    .duration_since(std::time::UNIX_EPOCH)
                    .expect("Failed to create array")
                    .as_nanos()
            ),
            data: vec![F::zero(); size],
            sharing_strategy: SharingStrategy::SharedReadWrite,
            replacement_policy: ReplacementPolicy::Adaptive,
            performance_metrics: CachePerformanceMetrics::new(),
        };

        hierarchy
            .l3_buffers
            .insert(buffer.id.clone(), buffer.clone());

        Ok(OptimizedMemoryRegion {
            id: buffer.id,
            memory_tier: MemoryTier::L3Cache,
            size,
            alignment: 64,
            optimization_applied: vec![
                "L3CacheOptimized".to_string(),
                "SharedMemoryOptimized".to_string(),
            ],
            _phantom: PhantomData,
        })
    }

    /// Allocate NUMA-optimized main memory
    fn allocate_numa_optimized(
        &self,
        size: usize,
        strategy: AllocationStrategy,
    ) -> IntegrateResult<OptimizedMemoryRegion<F>> {
        let numa_manager = self.numa_manager.read().expect("Operation failed");
        let optimal_node = NumaTopologyManager::select_optimal_node(size)?;
        drop(numa_manager);

        let mut hierarchy = self.hierarchy_manager.write().expect("Operation failed");

        let buffer = RamBuffer {
            id: format!(
                "ram_buffer_{}",
                std::time::SystemTime::now()
                    .duration_since(std::time::UNIX_EPOCH)
                    .expect("Failed to create array")
                    .as_nanos()
            ),
            data: vec![F::zero(); size],
            numa_node: optimal_node,
            bandwidth_usage: 0.0,
            use_large_pages: size > 2 * 1024 * 1024, // Use large pages for >2MB allocations
        };

        hierarchy
            .ram_buffers
            .insert(buffer.id.clone(), buffer.clone());

        Ok(OptimizedMemoryRegion {
            id: buffer.id,
            memory_tier: MemoryTier::MainMemory,
            size,
            alignment: if buffer.use_large_pages {
                2 * 1024 * 1024
            } else {
                4096
            },
            optimization_applied: vec![
                "NumaOptimized".to_string(),
                if buffer.use_large_pages {
                    "LargePagesEnabled"
                } else {
                    "StandardPages"
                }
                .to_string(),
            ],
            _phantom: PhantomData,
        })
    }

    /// Allocate GPU-optimized memory
    fn allocate_gpu_optimized(
        &self,
        size: usize,
        strategy: AllocationStrategy,
    ) -> IntegrateResult<OptimizedMemoryRegion<F>> {
        let mut hierarchy = self.hierarchy_manager.write().expect("Operation failed");

        let buffer = GpuBuffer {
            id: format!(
                "gpu_buffer_{}",
                std::time::SystemTime::now()
                    .duration_since(std::time::UNIX_EPOCH)
                    .expect("Failed to create array")
                    .as_nanos()
            ),
            device_id: 0, // Default to first GPU
            _phantom: PhantomData,
            memory_type: AdvancedMemoryOptimizer::<F>::select_optimal_gpu_memory_type(size)?,
            size,
            coherency_state: CoherencyState::Coherent,
        };

        hierarchy
            .gpu_buffers
            .insert(buffer.id.clone(), buffer.clone());

        Ok(OptimizedMemoryRegion {
            id: buffer.id,
            memory_tier: MemoryTier::GpuMemory,
            size,
            alignment: 256, // GPU memory alignment
            optimization_applied: vec!["GpuOptimized".to_string(), "CoherencyManaged".to_string()],
            _phantom: PhantomData,
        })
    }

    /// Select optimal GPU memory type based on size and usage
    fn select_optimal_gpu_memory_type(size: usize) -> IntegrateResult<GpuMemoryType> {
        // Simple heuristic - would be more sophisticated in practice
        if size < 48 * 1024 {
            // < 48KB
            Ok(GpuMemoryType::Shared)
        } else if size < 64 * 1024 {
            // < 64KB
            Ok(GpuMemoryType::Constant)
        } else {
            Ok(GpuMemoryType::Global)
        }
    }

    /// Infer access pattern from method type
    fn infer_access_pattern(&self, methodtype: &str) -> IntegrateResult<AccessPattern> {
        match methodtype.to_lowercase().as_str() {
            "rk4" | "rk45" | "rk23" => Ok(AccessPattern::Sequential),
            "bdf" | "lsoda" => Ok(AccessPattern::Random), // Due to Jacobian operations
            "symplectic" => Ok(AccessPattern::Blocked { block_size: 1024 }),
            _ => Ok(AccessPattern::Sequential),
        }
    }

    /// Estimate computational intensity
    fn estimate_computational_intensity(&self, methodtype: &str) -> IntegrateResult<f64> {
        match methodtype.to_lowercase().as_str() {
            "rk4" => Ok(4.0),   // 4 function evaluations per step
            "rk45" => Ok(6.0),  // 6 function evaluations per step
            "bdf" => Ok(2.0),   // Implicit method, fewer evaluations but more linear algebra
            "lsoda" => Ok(3.0), // Adaptive between methods
            _ => Ok(4.0),
        }
    }

    /// Analyze data locality characteristics
    fn analyze_data_locality(&self, problemsize: usize) -> IntegrateResult<f64> {
        // Simple heuristic based on problem size
        if problemsize < 1000 {
            Ok(0.9) // High locality for small problems
        } else if problemsize < 100000 {
            Ok(0.6) // Medium locality
        } else {
            Ok(0.3) // Lower locality for large problems
        }
    }

    /// Assess parallelism potential
    fn assess_parallelism(&self, methodtype: &str) -> IntegrateResult<f64> {
        match methodtype.to_lowercase().as_str() {
            "rk4" | "rk45" | "rk23" => Ok(0.8), // High parallelism in explicit methods
            "bdf" => Ok(0.4),                   // Limited by linear solves
            "lsoda" => Ok(0.6),                 // Mixed
            _ => Ok(0.5),
        }
    }

    // Helper method implementations (simplified for brevity)
    fn design_optimal_layout(
        &self,
        self_requirements: &MemoryRequirements<F>,
    ) -> IntegrateResult<MemoryLayout> {
        Ok(MemoryLayout::SoA) // Structure of Arrays for better vectorization
    }

    fn design_cache_strategy(
        &self,
        self_requirements: &MemoryRequirements<F>,
    ) -> IntegrateResult<CacheStrategy> {
        Ok(CacheStrategy::Adaptive)
    }

    fn design_numa_placement(
        &self,
        self_requirements: &MemoryRequirements<F>,
    ) -> IntegrateResult<NumaPlacement> {
        Ok(NumaPlacement::LocalFirst)
    }

    fn design_prefetch_schedule(
        &self,
        self_requirements: &MemoryRequirements<F>,
        _iterations: usize,
    ) -> IntegrateResult<PrefetchSchedule> {
        Ok(PrefetchSchedule::Adaptive)
    }

    fn design_buffer_reuse(
        &self,
        self_requirements: &MemoryRequirements<F>,
    ) -> IntegrateResult<BufferReuseStrategy> {
        Ok(BufferReuseStrategy::LRU)
    }
}

// Supporting types and structures (simplified implementations)

#[derive(Debug, Clone)]
pub struct OptimizedMemoryRegion<F: IntegrateFloat> {
    pub id: String,
    pub memory_tier: MemoryTier,
    pub size: usize,
    pub alignment: usize,
    pub optimization_applied: Vec<String>,
    /// Phantom data for type parameter
    _phantom: PhantomData<F>,
}

#[derive(Debug, Clone)]
pub enum MemoryTier {
    L1Cache,
    L2Cache,
    L3Cache,
    MainMemory,
    GpuMemory,
}

#[derive(Debug, Clone)]
pub struct AllocationStrategy {
    pub memory_tier: MemoryTier,
    pub access_pattern: AccessPattern,
    pub prefetch_strategy: PrefetchStrategy,
    pub memory_layout: MemoryLayout,
}

#[derive(Debug, Clone)]
pub struct ProblemCharacteristics {
    pub dimension: usize,
    pub estimated_memory_footprint: usize,
    pub access_pattern: AccessPattern,
    pub computational_intensity: f64,
    pub data_locality: f64,
    pub parallelism_potential: f64,
}

#[derive(Debug, Clone)]
pub struct MemoryRequirements<F: IntegrateFloat> {
    pub total_size: usize,
    pub working_set_size: usize,
    pub peak_usage: usize,
    pub temporal_pattern: TemporalAccessPattern,
    pub phantom: std::marker::PhantomData<F>,
}

#[derive(Debug, Clone)]
pub enum TemporalAccessPattern {
    Uniform,
    Bursty,
    Periodic,
    Random,
}

#[derive(Debug, Clone)]
pub struct OptimizationPlan<F: IntegrateFloat> {
    pub memory_layout: MemoryLayout,
    pub cache_strategy: CacheStrategy,
    pub numa_placement: NumaPlacement,
    pub prefetch_schedule: PrefetchSchedule,
    pub buffer_reuse_plan: BufferReuseStrategy,
    pub optimization_applied: Vec<String>,
    /// Phantom data for type parameter
    _phantom: PhantomData<F>,
}

#[derive(Debug, Clone)]
pub enum CacheStrategy {
    Aggressive,
    Conservative,
    Adaptive,
}

#[derive(Debug, Clone)]
pub enum NumaPlacement {
    LocalFirst,
    RoundRobin,
    BandwidthOptimized,
}

#[derive(Debug, Clone)]
pub enum PrefetchSchedule {
    None,
    Fixed,
    Adaptive,
}

#[derive(Debug, Clone)]
pub enum BufferReuseStrategy {
    LRU,
    LFU,
    Optimal,
}

// Placeholder implementations for complex types

impl<F: IntegrateFloat> MemoryHierarchyManager<F> {
    fn new() -> IntegrateResult<Self> {
        Ok(MemoryHierarchyManager {
            l1_buffers: HashMap::new(),
            l2_buffers: HashMap::new(),
            l3_buffers: HashMap::new(),
            ram_buffers: HashMap::new(),
            gpu_buffers: HashMap::new(),
            usage_stats: MemoryUsageStatistics::new(),
            cache_info: CacheHierarchyInfo::detect()?,
        })
    }
}

impl<F: IntegrateFloat> AllocationPredictor<F> {
    fn new() -> Self {
        AllocationPredictor {
            allocation_history: VecDeque::new(),
            problem_analyzer: ProblemCharacteristicAnalyzer::new(),
            pattern_models: HashMap::new(),
            accuracy_tracker: PredictionAccuracyTracker::new(),
        }
    }

    fn predict_optimal_allocation(
        &self,
        size: usize,
        _memory_type: MemoryType,
    ) -> IntegrateResult<AllocationStrategy> {
        // Simplified prediction logic
        let memory_tier = if size < 1024 {
            MemoryTier::L1Cache
        } else if size < 64 * 1024 {
            MemoryTier::L2Cache
        } else if size < 8 * 1024 * 1024 {
            MemoryTier::L3Cache
        } else {
            MemoryTier::MainMemory
        };

        Ok(AllocationStrategy {
            memory_tier,
            access_pattern: AccessPattern::Sequential,
            prefetch_strategy: PrefetchStrategy::Adaptive,
            memory_layout: MemoryLayout::SoA,
        })
    }

    fn predict_requirements(
        &self,
        characteristics: &ProblemCharacteristics,
    ) -> IntegrateResult<MemoryRequirements<F>> {
        Ok(MemoryRequirements {
            total_size: characteristics.estimated_memory_footprint,
            working_set_size: characteristics.estimated_memory_footprint / 2,
            peak_usage: characteristics.estimated_memory_footprint * 3 / 2,
            temporal_pattern: TemporalAccessPattern::Uniform,
            phantom: std::marker::PhantomData,
        })
    }
}

impl<F: IntegrateFloat> CacheOptimizer<F> {
    fn new() -> IntegrateResult<Self> {
        Ok(CacheOptimizer {
            algorithm_selector: CacheAwareAlgorithmSelector::new(),
            layout_optimizer: DataLayoutOptimizer::new(),
            blocking_manager: CacheBlockingManager::new(),
            prefetch_optimizer: PrefetchPatternOptimizer::new(),
        })
    }

    fn apply_optimizations(plan: &OptimizationPlan<F>) -> IntegrateResult<()> {
        // Implementation would apply various cache optimizations
        Ok(())
    }
}

impl RealTimeMemoryMonitor {
    fn new() -> IntegrateResult<Self> {
        Ok(RealTimeMemoryMonitor {
            usage_tracker: MemoryUsageTracker::new(),
            perf_counters: PerformanceCounters::new()?,
            leak_detector: MemoryLeakDetector::new(),
            fragmentation_analyzer: FragmentationAnalyzer::new(),
        })
    }
}

impl NumaTopologyManager {
    fn new() -> IntegrateResult<Self> {
        Ok(NumaTopologyManager {
            topology: NumaTopology::detect()?,
            placement_policies: HashMap::new(),
            node_bandwidths: Array2::zeros((1, 1)),
            cpu_affinity: CpuAffinityManager::new(),
        })
    }

    fn select_optimal_node(size: usize) -> IntegrateResult<usize> {
        // Simplified - return first node
        Ok(0)
    }
}

impl<F: IntegrateFloat> ZeroCopyBufferPool<F> {
    fn new() -> IntegrateResult<Self> {
        Ok(ZeroCopyBufferPool {
            available_buffers: Vec::new(),
            allocated_buffers: HashMap::new(),
            mmap_buffers: Vec::new(),
            reuse_stats: BufferReuseStatistics::new(),
        })
    }
}

/// Memory usage statistics
#[derive(Debug, Clone, Default)]
pub struct MemoryUsageStatistics {
    pub total_allocated: usize,
    pub peak_usage: usize,
    pub current_usage: usize,
}

impl MemoryUsageStatistics {
    pub fn new() -> Self {
        Default::default()
    }
}

/// Cache hierarchy information
#[derive(Debug, Clone)]
pub struct CacheHierarchyInfo {
    pub l1_size: usize,
    pub l2_size: usize,
    pub l3_size: usize,
    pub cache_line_size: usize,
}

impl CacheHierarchyInfo {
    pub fn new() -> Self {
        Default::default()
    }

    pub fn detect() -> IntegrateResult<Self> {
        Ok(Self {
            l1_size: 32 * 1024,       // 32KB L1 cache
            l2_size: 256 * 1024,      // 256KB L2 cache
            l3_size: 8 * 1024 * 1024, // 8MB L3 cache
            cache_line_size: 64,      // 64-byte cache lines
        })
    }
}

impl Default for CacheHierarchyInfo {
    fn default() -> Self {
        Self {
            l1_size: 32 * 1024,
            l2_size: 256 * 1024,
            l3_size: 8 * 1024 * 1024,
            cache_line_size: 64,
        }
    }
}

/// Buffer usage statistics
#[derive(Debug, Clone, Default)]
pub struct BufferUsageStats {
    pub access_count: usize,
    pub hit_rate: f64,
    pub miss_rate: f64,
}

impl BufferUsageStats {
    pub fn new() -> Self {
        Default::default()
    }
}

/// Cache performance metrics
#[derive(Debug, Clone, Default)]
pub struct CachePerformanceMetrics {
    pub hit_rate: f64,
    pub miss_rate: f64,
    pub eviction_rate: f64,
}

impl CachePerformanceMetrics {
    pub fn new() -> Self {
        Default::default()
    }
}

/// Allocation pattern information
#[derive(Debug, Clone, Default)]
pub struct AllocationPattern {
    pub pattern_type: String,
    pub frequency: f64,
    pub performance_impact: f64,
}

impl AllocationPattern {
    pub fn new() -> Self {
        Default::default()
    }
}

/// Prediction accuracy tracker
#[derive(Debug, Clone, Default)]
pub struct PredictionAccuracyTracker {
    pub accuracy: f64,
    pub predictions_made: usize,
    pub correct_predictions: usize,
}

impl PredictionAccuracyTracker {
    pub fn new() -> Self {
        Default::default()
    }
}

// Proper implementations for supporting types

/// Dimension analyzer for problem size characteristics
#[derive(Debug, Clone, Default)]
pub struct DimensionAnalyzer {
    max_dimension_seen: usize,
    dimension_history: Vec<usize>,
}

/// Sparsity pattern analyzer
#[derive(Debug, Clone, Default)]
pub struct SparsityAnalyzer {
    sparsity_patterns: Vec<f64>,
    nnz_ratios: Vec<f64>,
}

/// Temporal access pattern analyzer
#[derive(Debug, Clone, Default)]
pub struct TemporalAnalyzer {
    access_timestamps: Vec<Instant>,
    pattern_frequency: HashMap<String, usize>,
}

/// Stiffness characteristic analyzer
#[derive(Debug, Clone, Default)]
pub struct StiffnessAnalyzer {
    stiffness_ratios: Vec<f64>,
    eigenvalue_estimates: Vec<f64>,
}

/// Cache-aware algorithm selector
#[derive(Debug, Clone, Default)]
pub struct CacheAwareAlgorithmSelector {
    algorithm_performance: HashMap<String, f64>,
    cache_efficiency_metrics: HashMap<String, f64>,
}

/// Data layout optimizer
#[derive(Debug, Clone)]
pub struct DataLayoutOptimizer<F: IntegrateFloat> {
    layout_performance: HashMap<String, f64>,
    optimization_history: Vec<MemoryLayout>,
    _phantom: std::marker::PhantomData<F>,
}

impl<F: IntegrateFloat> Default for DataLayoutOptimizer<F> {
    fn default() -> Self {
        Self {
            layout_performance: HashMap::new(),
            optimization_history: Vec::new(),
            _phantom: std::marker::PhantomData,
        }
    }
}

/// Cache blocking strategy manager
#[derive(Debug, Clone, Default)]
pub struct CacheBlockingManager {
    block_sizes: HashMap<String, usize>,
    performance_metrics: HashMap<String, f64>,
}

/// Prefetch pattern optimizer
#[derive(Debug, Clone, Default)]
pub struct PrefetchPatternOptimizer {
    pattern_performance: HashMap<String, f64>,
    optimal_distances: HashMap<String, usize>,
}

/// Memory usage tracker
#[derive(Debug, Clone, Default)]
pub struct MemoryUsageTracker {
    current_usage: usize,
    peak_usage: usize,
    allocation_timeline: Vec<(Instant, usize)>,
}

/// Memory leak detector
#[derive(Debug, Clone, Default)]
pub struct MemoryLeakDetector {
    active_allocations: HashMap<usize, (Instant, usize)>,
    suspected_leaks: Vec<usize>,
}

/// Fragmentation analyzer
#[derive(Debug, Clone, Default)]
pub struct FragmentationAnalyzer {
    fragmentation_ratio: f64,
    free_block_sizes: Vec<usize>,
}

/// NUMA topology information
#[derive(Debug, Clone, Default)]
pub struct NumaTopology {
    num_nodes: usize,
    node_distances: Vec<Vec<usize>>,
    memory_per_node: Vec<usize>,
}

/// CPU affinity manager
#[derive(Debug, Clone, Default)]
pub struct CpuAffinityManager {
    cpu_assignments: HashMap<usize, Vec<usize>>,
    numa_node_cpus: HashMap<usize, Vec<usize>>,
}

/// Buffer reuse statistics
#[derive(Debug, Clone, Default)]
pub struct BufferReuseStatistics {
    reuse_count: usize,
    total_allocations: usize,
    average_lifetime: Duration,
}

/// Performance counters
#[derive(Debug, Clone, Default)]
pub struct PerformanceCounters {
    cache_misses: u64,
    cache_hits: u64,
    tlb_misses: u64,
    branch_mispredictions: u64,
}

/// Memory placement policy
#[derive(Debug, Clone, Default)]
pub struct MemoryPlacementPolicy {
    policy_type: String,
    preferred_nodes: Vec<usize>,
    fallback_strategy: String,
}

// Implement new() methods for all types
impl DimensionAnalyzer {
    pub fn new() -> Self {
        Default::default()
    }
}

impl SparsityAnalyzer {
    pub fn new() -> Self {
        Default::default()
    }
}

impl TemporalAnalyzer {
    pub fn new() -> Self {
        Default::default()
    }
}

impl StiffnessAnalyzer {
    pub fn new() -> Self {
        Default::default()
    }
}

impl CacheAwareAlgorithmSelector {
    pub fn new() -> Self {
        Default::default()
    }
}

impl<F: IntegrateFloat> DataLayoutOptimizer<F> {
    pub fn new() -> Self {
        Default::default()
    }
}

impl CacheBlockingManager {
    pub fn new() -> Self {
        Default::default()
    }
}

impl PrefetchPatternOptimizer {
    pub fn new() -> Self {
        Default::default()
    }
}

impl MemoryUsageTracker {
    pub fn new() -> Self {
        Default::default()
    }
}

impl MemoryLeakDetector {
    pub fn new() -> Self {
        Default::default()
    }
}

impl FragmentationAnalyzer {
    pub fn new() -> Self {
        Default::default()
    }
}

impl NumaTopology {
    pub fn new() -> Self {
        Default::default()
    }

    pub fn detect() -> IntegrateResult<Self> {
        Ok(Self {
            num_nodes: 1,
            node_distances: vec![vec![0]],
            memory_per_node: vec![1024 * 1024 * 1024], // 1GB default
        })
    }
}

impl CpuAffinityManager {
    pub fn new() -> Self {
        Default::default()
    }
}

impl BufferReuseStatistics {
    pub fn new() -> Self {
        Default::default()
    }
}

impl PerformanceCounters {
    pub fn new() -> IntegrateResult<Self> {
        Ok(Default::default())
    }
}

impl ProblemCharacteristicAnalyzer {
    pub fn new() -> Self {
        Self {
            dimension_analyzer: DimensionAnalyzer::new(),
            sparsity_analyzer: SparsityAnalyzer::new(),
            temporal_analyzer: TemporalAnalyzer::new(),
            stiffness_analyzer: StiffnessAnalyzer::new(),
        }
    }
}

impl Default for ProblemCharacteristicAnalyzer {
    fn default() -> Self {
        Self::new()
    }
}

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

    #[test]
    fn test_advanced_memory_optimizer_creation() {
        let optimizer = AdvancedMemoryOptimizer::<f64>::new();
        assert!(optimizer.is_ok());
    }

    #[test]
    fn test_memory_allocation_prediction() {
        let optimizer = AdvancedMemoryOptimizer::<f64>::new().expect("Operation failed");
        let plan = optimizer.optimize_for_problem(1000, "rk4", 100);
        assert!(plan.is_ok());
    }

    #[test]
    fn test_solution_memory_allocation() {
        let optimizer = AdvancedMemoryOptimizer::<f64>::new().expect("Operation failed");
        let memory = optimizer.allocate_solution_memory(1000);
        assert!(memory.is_ok());
    }
}