quantrs2-device 0.1.3

Quantum device connectors for the QuantRS2 framework
Documentation
//! Hardware-aware parallelization engine

use super::config::*;
use super::monitor::*;
use super::types::*;
use crate::{
    calibration::CalibrationManager, integrated_device_manager::IntegratedQuantumDeviceManager,
    routing_advanced::AdvancedQubitRouter, translation::HardwareBackend, DeviceResult,
};
use quantrs2_circuit::prelude::*;
use quantrs2_core::qubit::QubitId;
use std::collections::{HashMap, VecDeque};
use std::sync::{Arc, RwLock};
use std::time::{Duration, SystemTime};
use tokio::sync::{Mutex as AsyncMutex, Semaphore};

/// Main hardware-aware parallelization engine
pub struct HardwareParallelizationEngine {
    config: ParallelizationConfig,
    device_manager: Arc<RwLock<IntegratedQuantumDeviceManager>>,
    calibration_manager: Arc<RwLock<CalibrationManager>>,
    router: Arc<RwLock<AdvancedQubitRouter>>,
    // Execution pools
    circuit_pool: Arc<AsyncMutex<VecDeque<ParallelCircuitTask>>>,
    gate_pool: Arc<AsyncMutex<VecDeque<ParallelGateTask>>>,
    // Resource tracking
    resource_monitor: Arc<RwLock<ResourceMonitor>>,
    // Performance tracking
    performance_tracker: Arc<RwLock<PerformanceTracker>>,
    // Load balancer
    load_balancer: Arc<RwLock<LoadBalancer>>,
    // Semaphores for resource control
    circuit_semaphore: Arc<Semaphore>,
    gate_semaphore: Arc<Semaphore>,
    memory_semaphore: Arc<Semaphore>,
}

impl HardwareParallelizationEngine {
    /// Create a new hardware parallelization engine
    pub fn new(
        config: ParallelizationConfig,
        device_manager: Arc<RwLock<IntegratedQuantumDeviceManager>>,
        calibration_manager: Arc<RwLock<CalibrationManager>>,
        router: Arc<RwLock<AdvancedQubitRouter>>,
    ) -> Self {
        let circuit_semaphore = Arc::new(Semaphore::new(
            config.resource_allocation.max_concurrent_circuits,
        ));
        let gate_semaphore = Arc::new(Semaphore::new(
            config.resource_allocation.max_concurrent_gates,
        ));
        let memory_semaphore = Arc::new(Semaphore::new(
            (config.resource_allocation.memory_limits.max_total_memory_mb
                / config.resource_allocation.memory_limits.max_per_circuit_mb) as usize,
        ));

        Self {
            config: config.clone(),
            device_manager,
            calibration_manager,
            router,
            circuit_pool: Arc::new(AsyncMutex::new(VecDeque::new())),
            gate_pool: Arc::new(AsyncMutex::new(VecDeque::new())),
            resource_monitor: Arc::new(RwLock::new(ResourceMonitor::new())),
            performance_tracker: Arc::new(RwLock::new(PerformanceTracker::new())),
            load_balancer: Arc::new(RwLock::new(LoadBalancer::new(
                config.load_balancing.algorithm,
            ))),
            circuit_semaphore,
            gate_semaphore,
            memory_semaphore,
        }
    }

    /// Submit a circuit for parallel execution
    pub async fn submit_parallel_circuit<const N: usize>(
        &self,
        circuit: Circuit<N>,
        target_backend: HardwareBackend,
        priority: TaskPriority,
        constraints: ExecutionConstraints,
    ) -> DeviceResult<String> {
        let task_id = uuid::Uuid::new_v4().to_string();

        // Calculate resource requirements
        let resource_requirements =
            self.calculate_resource_requirements(&circuit, &target_backend)?;

        // Create parallel task
        let task = ParallelCircuitTask {
            id: task_id.clone(),
            circuit: Box::new(circuit),
            target_backend,
            priority,
            resource_requirements,
            constraints,
            submitted_at: SystemTime::now(),
            deadline: None, // Will be set based on constraints
        };

        // Add to circuit pool
        {
            let mut pool = self.circuit_pool.lock().await;
            pool.push_back(task);
        }

        // Trigger scheduling
        self.schedule_circuits().await?;

        Ok(task_id)
    }

    /// Submit gates for parallel execution
    pub async fn submit_parallel_gates(
        &self,
        gate_operations: Vec<ParallelGateOperation>,
        target_qubits: Vec<QubitId>,
        priority: TaskPriority,
    ) -> DeviceResult<String> {
        let task_id = uuid::Uuid::new_v4().to_string();

        // Build dependency graph
        let dependency_graph = self.build_dependency_graph(&gate_operations)?;

        // Create parallel gate task
        let task = ParallelGateTask {
            id: task_id.clone(),
            gate_operations,
            target_qubits,
            dependency_graph,
            priority,
            submitted_at: SystemTime::now(),
        };

        // Add to gate pool
        {
            let mut pool = self.gate_pool.lock().await;
            pool.push_back(task);
        }

        // Trigger gate scheduling
        self.schedule_gates().await?;

        Ok(task_id)
    }

    /// Execute parallel circuits using the configured strategy
    pub async fn execute_parallel_circuits(&self) -> DeviceResult<Vec<ParallelExecutionResult>> {
        match self.config.strategy {
            ParallelizationStrategy::CircuitLevel => {
                self.execute_circuit_level_parallelization().await
            }
            ParallelizationStrategy::GateLevel => self.execute_gate_level_parallelization().await,
            ParallelizationStrategy::Hybrid => self.execute_hybrid_parallelization().await,
            ParallelizationStrategy::TopologyAware => {
                self.execute_topology_aware_parallelization().await
            }
            ParallelizationStrategy::ResourceConstrained => {
                self.execute_resource_constrained_parallelization().await
            }
            ParallelizationStrategy::SciRS2Optimized => {
                self.execute_scirs2_optimized_parallelization().await
            }
            ParallelizationStrategy::Custom { .. } => self.execute_custom_parallelization().await,
        }
    }

    /// Get current performance metrics
    pub async fn get_performance_metrics(
        &self,
    ) -> DeviceResult<super::monitor::PerformanceMetrics> {
        let tracker = self.performance_tracker.read().map_err(|_| {
            crate::DeviceError::LockError(
                "Failed to acquire read lock on performance tracker".into(),
            )
        })?;
        Ok(tracker.performance_metrics.clone())
    }

    /// Get optimization suggestions
    pub async fn get_optimization_suggestions(
        &self,
    ) -> DeviceResult<Vec<super::monitor::OptimizationSuggestion>> {
        let tracker = self.performance_tracker.read().map_err(|_| {
            crate::DeviceError::LockError(
                "Failed to acquire read lock on performance tracker".into(),
            )
        })?;
        Ok(tracker.optimization_suggestions.clone())
    }

    /// Apply dynamic load balancing
    #[allow(clippy::await_holding_lock)] // Placeholder implementation - to be refactored
    pub async fn apply_load_balancing(&self) -> DeviceResult<LoadBalancingResult> {
        let mut balancer = self.load_balancer.write().map_err(|_| {
            crate::DeviceError::LockError("Failed to acquire write lock on load balancer".into())
        })?;
        balancer.rebalance_loads().await
    }

    // Private implementation methods...

    async fn schedule_circuits(&self) -> DeviceResult<()> {
        // Implementation for circuit scheduling
        Ok(())
    }

    async fn schedule_gates(&self) -> DeviceResult<()> {
        // Implementation for gate scheduling
        Ok(())
    }

    const fn calculate_resource_requirements<const N: usize>(
        &self,
        circuit: &Circuit<N>,
        backend: &HardwareBackend,
    ) -> DeviceResult<ParallelResourceRequirements> {
        // Implementation for resource requirement calculation
        Ok(ParallelResourceRequirements {
            required_cpu_cores: 1,
            required_memory_mb: 512.0,
            required_qpu_time: Duration::from_secs(60),
            required_bandwidth_mbps: 10.0,
            required_storage_mb: 100.0,
        })
    }

    fn build_dependency_graph(
        &self,
        operations: &[ParallelGateOperation],
    ) -> DeviceResult<HashMap<String, Vec<String>>> {
        // Implementation for dependency graph building
        Ok(HashMap::new())
    }

    async fn execute_circuit_level_parallelization(
        &self,
    ) -> DeviceResult<Vec<ParallelExecutionResult>> {
        // Implementation for circuit-level parallelization
        Ok(vec![])
    }

    async fn execute_gate_level_parallelization(
        &self,
    ) -> DeviceResult<Vec<ParallelExecutionResult>> {
        // Implementation for gate-level parallelization
        Ok(vec![])
    }

    async fn execute_hybrid_parallelization(&self) -> DeviceResult<Vec<ParallelExecutionResult>> {
        // Implementation for hybrid parallelization
        Ok(vec![])
    }

    async fn execute_topology_aware_parallelization(
        &self,
    ) -> DeviceResult<Vec<ParallelExecutionResult>> {
        // Implementation for topology-aware parallelization
        Ok(vec![])
    }

    async fn execute_resource_constrained_parallelization(
        &self,
    ) -> DeviceResult<Vec<ParallelExecutionResult>> {
        // Implementation for resource-constrained parallelization
        Ok(vec![])
    }

    async fn execute_scirs2_optimized_parallelization(
        &self,
    ) -> DeviceResult<Vec<ParallelExecutionResult>> {
        // Implementation for SciRS2-optimized parallelization
        Ok(vec![])
    }

    async fn execute_custom_parallelization(&self) -> DeviceResult<Vec<ParallelExecutionResult>> {
        // Implementation for custom parallelization
        Ok(vec![])
    }
}