quantrs2-anneal 0.1.3

//! Parallel processing types for scientific performance optimization.
//!
//! This module contains thread pools, task scheduling, load balancing,
//! and parallel performance metrics.

use std::collections::{HashMap, VecDeque};
use std::sync::{Arc, Mutex};
use std::thread;
use std::time::{Duration, Instant};

use crate::applications::protein_folding::ProteinSequence;

use super::config::{LoadBalancingStrategy, ParallelProcessingConfig, TaskSchedulingStrategy};

/// Advanced parallel processor
pub struct AdvancedParallelProcessor {
    /// Configuration
    pub config: ParallelProcessingConfig,
    /// Thread pool
    pub thread_pool: ThreadPool,
    /// Task scheduler
    pub task_scheduler: TaskScheduler,
    /// Load balancer
    pub load_balancer: LoadBalancer,
    /// Performance metrics
    pub performance_metrics: ParallelPerformanceMetrics,
}

impl AdvancedParallelProcessor {
    /// Create a new parallel processor
    #[must_use]
    pub fn new(config: ParallelProcessingConfig) -> Self {
        Self {
            config,
            thread_pool: ThreadPool::new(num_cpus::get()),
            task_scheduler: TaskScheduler::new(),
            load_balancer: LoadBalancer::new(),
            performance_metrics: ParallelPerformanceMetrics::default(),
        }
    }
}

/// Thread pool implementation
#[derive(Debug)]
pub struct ThreadPool {
    /// Worker threads
    pub workers: Vec<WorkerThread>,
    /// Task queue
    pub task_queue: Arc<Mutex<VecDeque<Task>>>,
    /// Thread pool statistics
    pub statistics: ThreadPoolStatistics,
}

impl ThreadPool {
    /// Create a new thread pool
    #[must_use]
    pub fn new(size: usize) -> Self {
        Self {
            workers: Vec::with_capacity(size),
            task_queue: Arc::new(Mutex::new(VecDeque::new())),
            statistics: ThreadPoolStatistics::default(),
        }
    }

    /// Get the number of workers
    #[must_use]
    pub fn worker_count(&self) -> usize {
        self.workers.len()
    }

    /// Get pending task count
    #[must_use]
    pub fn pending_tasks(&self) -> usize {
        self.task_queue.lock().map(|q| q.len()).unwrap_or(0)
    }
}

/// Worker thread representation
#[derive(Debug)]
pub struct WorkerThread {
    /// Thread identifier
    pub id: usize,
    /// Thread handle
    pub handle: Option<thread::JoinHandle<()>>,
    /// Current task
    pub current_task: Option<String>,
    /// Thread statistics
    pub statistics: WorkerStatistics,
}

impl WorkerThread {
    /// Create a new worker thread
    #[must_use]
    pub fn new(id: usize) -> Self {
        Self {
            id,
            handle: None,
            current_task: None,
            statistics: WorkerStatistics::default(),
        }
    }

    /// Check if worker is busy
    #[must_use]
    pub fn is_busy(&self) -> bool {
        self.current_task.is_some()
    }
}

/// Task representation for parallel processing
#[derive(Debug)]
pub struct Task {
    /// Task identifier
    pub id: String,
    /// Task priority
    pub priority: TaskPriority,
    /// Task function
    pub function: TaskFunction,
    /// Task dependencies
    pub dependencies: Vec<String>,
    /// Estimated execution time
    pub estimated_time: Duration,
}

/// Task function types
#[derive(Debug)]
pub enum TaskFunction {
    /// Protein folding task
    ProteinFolding(ProteinFoldingTask),
    /// Materials science task
    MaterialsScience(MaterialsScienceTask),
    /// Drug discovery task
    DrugDiscovery(DrugDiscoveryTask),
    /// Generic computation task
    Generic(GenericTask),
}

/// Task priorities
#[derive(Debug, Clone, PartialEq, Eq, PartialOrd)]
pub enum TaskPriority {
    Low = 1,
    Medium = 2,
    High = 3,
    Critical = 4,
}

/// Protein folding specific task
#[derive(Debug)]
pub struct ProteinFoldingTask {
    /// Protein sequence
    pub sequence: ProteinSequence,
    /// Lattice parameters
    pub lattice_params: LatticeParameters,
    /// Optimization parameters
    pub optimization_params: OptimizationParameters,
}

/// Materials science specific task
#[derive(Debug)]
pub struct MaterialsScienceTask {
    /// Crystal structure
    pub crystal_structure: CrystalStructure,
    /// Simulation parameters
    pub simulation_params: SimulationParameters,
    /// Analysis requirements
    pub analysis_requirements: AnalysisRequirements,
}

/// Drug discovery specific task
#[derive(Debug)]
pub struct DrugDiscoveryTask {
    /// Molecular structure
    pub molecular_structure: String,
    /// Interaction targets
    pub targets: Vec<InteractionTarget>,
    /// Property constraints
    pub property_constraints: PropertyConstraints,
}

/// Generic computation task
#[derive(Debug)]
pub struct GenericTask {
    /// Task description
    pub description: String,
    /// Input data
    pub input_data: Vec<u8>,
    /// Computation type
    pub computation_type: ComputationType,
}

/// Task scheduler for intelligent task distribution
#[derive(Debug)]
pub struct TaskScheduler {
    /// Scheduling strategy
    pub strategy: TaskSchedulingStrategy,
    /// Task queue
    pub task_queue: VecDeque<Task>,
    /// Scheduled tasks
    pub scheduled_tasks: HashMap<String, ScheduledTask>,
    /// Scheduler statistics
    pub statistics: SchedulerStatistics,
}

impl TaskScheduler {
    /// Create a new task scheduler
    #[must_use]
    pub fn new() -> Self {
        Self {
            strategy: TaskSchedulingStrategy::WorkStealing,
            task_queue: VecDeque::new(),
            scheduled_tasks: HashMap::new(),
            statistics: SchedulerStatistics::default(),
        }
    }

    /// Add a task to the queue
    pub fn add_task(&mut self, task: Task) {
        self.task_queue.push_back(task);
    }

    /// Get next task based on strategy
    pub fn next_task(&mut self) -> Option<Task> {
        match self.strategy {
            TaskSchedulingStrategy::FIFO => self.task_queue.pop_front(),
            TaskSchedulingStrategy::Priority => {
                // Find highest priority task
                let mut best_idx = None;
                let mut best_priority = TaskPriority::Low;
                for (idx, task) in self.task_queue.iter().enumerate() {
                    if task.priority >= best_priority {
                        best_priority = task.priority.clone();
                        best_idx = Some(idx);
                    }
                }
                best_idx.and_then(|idx| self.task_queue.remove(idx))
            }
            _ => self.task_queue.pop_front(),
        }
    }
}

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

/// Scheduled task representation
#[derive(Debug)]
pub struct ScheduledTask {
    /// Task
    pub task: Task,
    /// Assigned worker
    pub assigned_worker: usize,
    /// Scheduled time
    pub scheduled_time: Instant,
    /// Expected completion
    pub expected_completion: Instant,
}

/// Load balancer for dynamic resource allocation
#[derive(Debug)]
pub struct LoadBalancer {
    /// Balancing strategy
    pub strategy: LoadBalancingStrategy,
    /// Worker loads
    pub worker_loads: HashMap<usize, WorkerLoad>,
    /// Balancing decisions
    pub decisions: VecDeque<BalancingDecision>,
    /// Balancer statistics
    pub statistics: LoadBalancerStatistics,
}

impl LoadBalancer {
    /// Create a new load balancer
    #[must_use]
    pub fn new() -> Self {
        Self {
            strategy: LoadBalancingStrategy::RoundRobin,
            worker_loads: HashMap::new(),
            decisions: VecDeque::new(),
            statistics: LoadBalancerStatistics::default(),
        }
    }

    /// Select best worker for a task
    #[must_use]
    pub fn select_worker(&self) -> Option<usize> {
        match self.strategy {
            LoadBalancingStrategy::LeastLoaded => self
                .worker_loads
                .iter()
                .min_by(|a, b| {
                    a.1.cpu_usage
                        .partial_cmp(&b.1.cpu_usage)
                        .unwrap_or(std::cmp::Ordering::Equal)
                })
                .map(|(id, _)| *id),
            LoadBalancingStrategy::RoundRobin => {
                // Simple round-robin would need state tracking
                self.worker_loads.keys().next().copied()
            }
            _ => self.worker_loads.keys().next().copied(),
        }
    }

    /// Update worker load
    pub fn update_load(&mut self, worker_id: usize, load: WorkerLoad) {
        self.worker_loads.insert(worker_id, load);
    }
}

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

/// Worker load information
#[derive(Debug, Clone)]
pub struct WorkerLoad {
    /// Worker identifier
    pub worker_id: usize,
    /// Current CPU usage
    pub cpu_usage: f64,
    /// Current memory usage
    pub memory_usage: f64,
    /// Task queue length
    pub queue_length: usize,
    /// Performance score
    pub performance_score: f64,
}

impl WorkerLoad {
    /// Create a new worker load
    #[must_use]
    pub fn new(worker_id: usize) -> Self {
        Self {
            worker_id,
            cpu_usage: 0.0,
            memory_usage: 0.0,
            queue_length: 0,
            performance_score: 1.0,
        }
    }

    /// Calculate overall load score
    #[must_use]
    pub fn load_score(&self) -> f64 {
        (self.cpu_usage + self.memory_usage) / 2.0 + self.queue_length as f64 * 0.1
    }
}

/// Load balancing decision
#[derive(Debug, Clone)]
pub struct BalancingDecision {
    /// Decision timestamp
    pub timestamp: Instant,
    /// Source worker
    pub source_worker: usize,
    /// Target worker
    pub target_worker: usize,
    /// Tasks moved
    pub tasks_moved: Vec<String>,
    /// Decision rationale
    pub rationale: String,
}

// Placeholder types for task parameters

/// Lattice parameters for protein folding
#[derive(Debug, Clone, Default)]
pub struct LatticeParameters {}

/// Optimization parameters
#[derive(Debug, Clone, Default)]
pub struct OptimizationParameters {}

/// Crystal structure for materials science
#[derive(Debug, Clone, Default)]
pub struct CrystalStructure {}

/// Defect analysis result
#[derive(Debug, Clone, Default)]
pub struct DefectAnalysisResult {}

/// Simulation parameters
#[derive(Debug, Clone, Default)]
pub struct SimulationParameters {}

/// Analysis requirements
#[derive(Debug, Clone, Default)]
pub struct AnalysisRequirements {}

/// Interaction target for drug discovery
#[derive(Debug, Clone, Default)]
pub struct InteractionTarget {}

/// Property constraints for drug discovery
#[derive(Debug, Clone, Default)]
pub struct PropertyConstraints {}

/// Computation types
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum ComputationType {
    Optimization,
    Simulation,
    Analysis,
}

// Statistics types

/// Parallel performance metrics
#[derive(Debug, Clone, Default)]
pub struct ParallelPerformanceMetrics {
    /// Parallel efficiency
    pub parallel_efficiency: f64,
    /// Total tasks completed
    pub tasks_completed: u64,
    /// Average task time
    pub avg_task_time: Duration,
    /// Throughput (tasks per second)
    pub throughput: f64,
}

/// Thread pool statistics
#[derive(Debug, Clone, Default)]
pub struct ThreadPoolStatistics {
    /// Total tasks submitted
    pub tasks_submitted: u64,
    /// Tasks completed
    pub tasks_completed: u64,
    /// Tasks failed
    pub tasks_failed: u64,
    /// Average wait time
    pub avg_wait_time: Duration,
}

/// Worker statistics
#[derive(Debug, Clone, Default)]
pub struct WorkerStatistics {
    /// Tasks executed
    pub tasks_executed: u64,
    /// Total execution time
    pub total_execution_time: Duration,
    /// Idle time
    pub idle_time: Duration,
    /// Errors encountered
    pub errors: u64,
}

/// Scheduler statistics
#[derive(Debug, Clone, Default)]
pub struct SchedulerStatistics {
    /// Tasks scheduled
    pub tasks_scheduled: u64,
    /// Rescheduling count
    pub rescheduling_count: u64,
    /// Average scheduling time
    pub avg_scheduling_time: Duration,
}

/// Load balancer statistics
#[derive(Debug, Clone, Default)]
pub struct LoadBalancerStatistics {
    /// Rebalancing events
    pub rebalancing_events: u64,
    /// Tasks migrated
    pub tasks_migrated: u64,
    /// Load variance
    pub load_variance: f64,
}