scirs2-linalg 0.4.0

//! MPI Integration Module
//!
//! This module provides a comprehensive MPI integration layer for distributed
//! linear algebra operations, organized into focused submodules for better
//! maintainability and modularity.

// Module declarations
pub mod backend;
pub mod communicator;
pub mod datatypes;
pub mod collective;
pub mod point_to_point;
pub mod topology;
pub mod profiling;
pub mod fault_tolerance;

// Re-export main types from each module

// Backend types
pub use backend::{
    MPIBackend, MPIConfig, MPIImplementation, BufferStrategy,
    CollectiveHints, MPIErrorHandling, MPIPerformanceTuning
};

// Communicator types
pub use communicator::{
    MPICommunicator, MPICommHandle, MPIPersistentRequest,
    PersistentOperationType, BufferInfo, MPIRequest,
    RequestOperationType, MPICommStats, MPIStatus
};

// Datatype types
pub use datatypes::{
    MPIDatatype, MPIReduceOp, DatatypeManager
};

// Collective operations types
pub use collective::{
    MPICollectiveOps, CollectiveOptimization,
    CollectivePerformanceRecord
};

// Point-to-point operations
pub use point_to_point::MPIPointToPoint;

// Topology types
pub use topology::{
    TreeTopology, MPITopologyManager, MPITopology, MPITopologyType,
    CommunicationGraph, EdgeProperties, VertexProperties,
    TopologyOptimizer, WorkloadCharacteristics, ComputationPattern,
    CommunicationPattern, NetworkTopologyInfo
};

// Profiling types
pub use profiling::{
    MPIPerformanceOptimizer, BenchmarkResult, AdaptiveParameters,
    MPIProfiler, MPITraceEvent, MPIEventType, MPITimeline,
    LoadBalanceAnalysis, MPIProfilingStats, MPIMeasurement,
    PerformanceReport, WorkloadProfile
};

// Fault tolerance types
pub use fault_tolerance::{
    MPIFaultTolerance, FaultToleranceConfig, RecoveryStrategy,
    MPICheckpointManager, CheckpointStorage, CheckpointMetadata,
    MPIFailureDetector, FailureDetectionStrategy, MPIRecoveryManager,
    SpareProcessManager, FailureType, HealthStatus
};

// Additional types that may be referenced
use crate::error::{LinalgError, LinalgResult};
use super::{
    DistributedConfig, DistributedMatrix, DistributedVector,
    CommunicationBackend, MessageTag, DistributedStats,
    CompressionAlgorithm, NetworkTopology
};
use scirs2_core::ndarray::{Array1, Array2, ArrayView1, ArrayView2};
use scirs2_core::numeric::{Float, NumAssign, Zero};
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::{Arc, Mutex, RwLock};

// Memory management structures that were in the original file
// These need to be included somewhere - let me add them here for now

/// Memory manager for efficient MPI operations
#[derive(Debug)]
pub struct MPIMemoryManager {
    memory_pools: HashMap<String, MemoryPool>,
    allocation_strategies: HashMap<String, AllocationStrategy>,
    memory_optimization: MemoryOptimization,
    usage_tracking: MemoryUsageTracking,
}

/// Memory pool for MPI operations
#[derive(Debug)]
pub struct MemoryPool {
    pool_id: String,
    memory_type: MPIMemoryType,
    allocated_blocks: HashMap<String, MemoryBlock>,
    free_blocks: Vec<MemoryBlock>,
    totalsize: usize,
    fragmentation: f64,
}

/// Types of MPI memory
#[derive(Debug, Clone, Copy)]
pub enum MPIMemoryType {
    Host,
    Pinned,
    Registered,
    Device,
    Unified,
}

/// Block of allocated memory
#[derive(Debug, Clone)]
pub struct MemoryBlock {
    block_id: String,
    start_address: *mut std::ffi::c_void,
    size: usize,
    memory_type: MPIMemoryType,
    allocation_time: std::time::Instant,
    last_access: std::time::Instant,
    access_count: usize,
}

/// Strategy for memory allocation
#[derive(Debug, Clone)]
pub enum AllocationStrategy {
    FirstFit,
    BestFit,
    WorstFit,
    BuddySystem,
    SlabAllocator,
    Custom(String),
}

/// Memory optimization techniques
#[derive(Debug)]
pub struct MemoryOptimization {
    enable_prefaulting: bool,
    enable_huge_pages: bool,
    enable_numa_awareness: bool,
    compression_strategies: HashMap<String, CompressionStrategy>,
    memory_recycling: MemoryRecycling,
}

/// Strategy for memory compression
#[derive(Debug, Clone)]
pub struct CompressionStrategy {
    algorithm: CompressionAlgorithm,
    thresholdsize: usize,
    compression_level: u8,
    decompression_on_access: bool,
}

/// Memory recycling configuration
#[derive(Debug, Clone)]
pub struct MemoryRecycling {
    enable_recycling: bool,
    idle_time_threshold: std::time::Duration,
    size_change_tolerance: f64,
    recycling_strategies: Vec<RecyclingStrategy>,
}

/// Strategy for memory recycling
#[derive(Debug, Clone, Copy)]
pub enum RecyclingStrategy {
    LeastRecentlyUsed,
    LeastFrequentlyUsed,
    SizeBased,
    AgeBased,
    AccessPatternBased,
}

/// Tracking of memory usage patterns
#[derive(Debug)]
pub struct MemoryUsageTracking {
    allocation_history: Vec<AllocationRecord>,
    usage_patterns: HashMap<String, UsagePattern>,
    performance_correlation: PerformanceCorrelation,
    optimization_suggestions: Vec<OptimizationSuggestion>,
}

/// Record of memory allocation
#[derive(Debug, Clone)]
pub struct AllocationRecord {
    timestamp: std::time::Instant,
    block_id: String,
    size: usize,
    memory_type: MPIMemoryType,
    requester: String,
    lifetime: Option<std::time::Duration>,
}

/// Pattern of memory usage
#[derive(Debug, Clone)]
pub struct UsagePattern {
    pattern_type: UsagePatternType,
    frequency: f64,
    typicalsize: usize,
    typical_lifetime: std::time::Duration,
    access_locality: f64,
}

/// Types of memory usage patterns
#[derive(Debug, Clone, Copy)]
pub enum UsagePatternType {
    Sequential,
    Random,
    Temporal,
    Spatial,
    Streaming,
    Batch,
}

/// Correlation between memory usage and performance
#[derive(Debug, Clone)]
pub struct PerformanceCorrelation {
    correlation_coefficient: f64,
    memory_bottlenecks: Vec<MemoryBottleneck>,
    performance_metrics: HashMap<String, f64>,
}

/// Memory-related performance bottleneck
#[derive(Debug, Clone)]
pub struct MemoryBottleneck {
    bottleneck_type: BottleneckType,
    severity: f64,
    affected_operations: Vec<String>,
    mitigation_strategies: Vec<String>,
}

/// Types of memory bottlenecks
#[derive(Debug, Clone, Copy)]
pub enum BottleneckType {
    Bandwidth,
    Latency,
    Fragmentation,
    Allocation,
    Deallocation,
    Contention,
}

/// Suggestion for memory optimization
#[derive(Debug, Clone)]
pub struct OptimizationSuggestion {
    suggestion_type: SuggestionType,
    priority: f64,
    expected_improvement: f64,
    implementation_effort: f64,
    description: String,
}

/// Types of optimization suggestions
#[derive(Debug, Clone, Copy)]
pub enum SuggestionType {
    ChangeAllocationStrategy,
    AdjustPoolSizes,
    EnableCompression,
    ImproveLocality,
    ReduceFragmentation,
    OptimizeLifetime,
}

// Implementation defaults for memory management
impl MPIMemoryManager {
    /// Create a new memory manager
    pub fn new() -> Self {
        Self {
            memory_pools: HashMap::new(),
            allocation_strategies: HashMap::new(),
            memory_optimization: MemoryOptimization::default(),
            usage_tracking: MemoryUsageTracking::default(),
        }
    }

    /// Get memory pools
    pub fn memory_pools(&self) -> &HashMap<String, MemoryPool> {
        &self.memory_pools
    }

    /// Get allocation strategies
    pub fn allocation_strategies(&self) -> &HashMap<String, AllocationStrategy> {
        &self.allocation_strategies
    }

    /// Get memory optimization settings
    pub fn memory_optimization(&self) -> &MemoryOptimization {
        &self.memory_optimization
    }

    /// Get usage tracking
    pub fn usage_tracking(&self) -> &MemoryUsageTracking {
        &self.usage_tracking
    }
}

impl Default for MemoryOptimization {
    fn default() -> Self {
        Self {
            enable_prefaulting: true,
            enable_huge_pages: false,
            enable_numa_awareness: true,
            compression_strategies: HashMap::new(),
            memory_recycling: MemoryRecycling::default(),
        }
    }
}

impl Default for MemoryRecycling {
    fn default() -> Self {
        Self {
            enable_recycling: true,
            idle_time_threshold: std::time::Duration::from_secs(300),
            size_change_tolerance: 0.1,
            recycling_strategies: vec![RecyclingStrategy::LeastRecentlyUsed],
        }
    }
}

impl Default for MemoryUsageTracking {
    fn default() -> Self {
        Self {
            allocation_history: Vec::new(),
            usage_patterns: HashMap::new(),
            performance_correlation: PerformanceCorrelation::default(),
            optimization_suggestions: Vec::new(),
        }
    }
}

impl Default for PerformanceCorrelation {
    fn default() -> Self {
        Self {
            correlation_coefficient: 0.0,
            memory_bottlenecks: Vec::new(),
            performance_metrics: HashMap::new(),
        }
    }
}

unsafe impl Send for MemoryBlock {}
unsafe impl Sync for MemoryBlock {}

// Additional supporting types that may be missing

/// Distributed matrix type (placeholder - should be defined elsewhere)
#[allow(dead_code)]
pub struct DistributedMatrix<T> {
    _phantom: std::marker::PhantomData<T>,
}

/// Data characteristics for communication optimization
#[derive(Debug, Default)]
pub struct DataCharacteristics {
    pub element_size: usize,
    pub matrix_dimensions: (usize, usize),
    pub sparsity: f64,
    pub access_pattern: String,
}

/// Workload analysis for intelligent process spawning
#[derive(Debug, Default)]
pub struct WorkloadAnalysis {
    pub computational_complexity: f64,
    pub memory_requirements: usize,
    pub communication_intensity: f64,
    pub parallelization_efficiency: f64,
}

/// System state for optimization decisions
#[derive(Debug, Default)]
pub struct SystemState {
    pub total_processes: u32,
    pub system_load: f64,
    pub memory_usage: f64,
    pub network_utilization: f64,
}

/// Workload prediction for load balancing
#[derive(Debug, Default)]
pub struct WorkloadPrediction {
    pub expected_operations: Vec<String>,
    pub datasizes: Vec<usize>,
    pub completion_deadlines: Vec<f64>,
}

/// Performance prediction results
#[derive(Debug, Default)]
pub struct PerformancePrediction {
    pub expected_throughput: f64,
    pub expected_latency: f64,
    pub resource_requirements: HashMap<String, f64>,
}

/// Load balancing plan
#[derive(Debug, Default)]
pub struct LoadBalancingPlan {
    pub process_assignments: HashMap<i32, Vec<String>>,
    pub migration_schedule: Vec<(i32, i32)>,
    pub expected_improvement: f64,
}

/// Communication requirements analysis
#[derive(Debug, Default)]
pub struct CommunicationRequirements {
    pub message_patterns: Vec<String>,
    pub data_volumes: Vec<usize>,
    pub latency_requirements: Vec<f64>,
}

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

    #[test]
    fn test_mpi_config_default() {
        let config = MPIConfig::default();
        assert_eq!(config.implementation, MPIImplementation::OpenMPI);
        assert!(config.non_blocking);
        assert!(config.persistent_requests);
    }

    #[test]
    fn test_mpi_reduce_op_conversion() {
        assert_eq!(MPIReduceOp::Sum.to_mpi_op(), 0);
        assert_eq!(MPIReduceOp::Max.to_mpi_op(), 2);
        assert_eq!(MPIReduceOp::Custom(42).to_mpi_op(), 42);
    }

    #[test]
    fn test_memory_manager_creation() {
        let manager = MPIMemoryManager::new();
        assert!(manager.memory_pools().is_empty());
        assert!(manager.allocation_strategies().is_empty());
    }

    #[test]
    fn test_fault_tolerance_config_default() {
        let config = FaultToleranceConfig::default();
        assert!(config.enable_checkpointing);
        assert!(config.enable_process_migration);
        assert!(config.enable_spare_processes);
        assert_eq!(config.checkpoint_frequency, std::time::Duration::from_secs(300));
    }
}