quantrs2_device/compiler_passes/

compiler.rs

//! Main hardware compiler implementation

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

use scirs2_core::ndarray::Array1;
use quantrs2_circuit::prelude::Circuit;

use crate::{
    backend_traits::BackendCapabilities, calibration::DeviceCalibration,
    crosstalk::CrosstalkCharacterization, noise_model::CalibrationNoiseModel,
    topology::HardwareTopology, DeviceError, DeviceResult,
};

use super::config::CompilerConfig;
use super::optimization::{CrosstalkModel, GlobalMitigationStrategy, SciRS2OptimizationEngine};
use super::passes::{PassCoordinator, PerformanceMonitor};
use super::types::*;

/// Advanced hardware compiler with SciRS2 integration
pub struct HardwareCompiler {
    /// Compiler configuration
    pub config: CompilerConfig,
    /// Hardware topology information
    pub topology: HardwareTopology,
    /// Device calibration data
    pub calibration: DeviceCalibration,
    /// Noise model derived from calibration
    pub noise_model: CalibrationNoiseModel,
    /// Crosstalk characterization data
    pub crosstalk_data: Option<CrosstalkCharacterization>,
    /// Backend capabilities
    pub backend_capabilities: BackendCapabilities,
    /// SciRS2 optimization engine
    pub scirs2_engine: Arc<SciRS2OptimizationEngine>,
    /// Performance monitoring
    pub performance_monitor: Arc<Mutex<PerformanceMonitor>>,
    /// Pass coordination
    pub pass_coordinator: PassCoordinator,
    /// Platform-specific optimizers
    pub platform_optimizers: HashMap<String, String>,
}

impl HardwareCompiler {
    /// Create a new advanced hardware compiler with SciRS2 integration
    pub fn new(
        config: CompilerConfig,
        topology: HardwareTopology,
        calibration: DeviceCalibration,
        crosstalk_data: Option<CrosstalkCharacterization>,
        backend_capabilities: BackendCapabilities,
    ) -> DeviceResult<Self> {
        let noise_model = CalibrationNoiseModel::from_calibration(&calibration);

        let scirs2_engine = Arc::new(SciRS2OptimizationEngine::new(&config.scirs2_config)?);
        let performance_monitor = Arc::new(Mutex::new(PerformanceMonitor::new()));
        let pass_coordinator = PassCoordinator::new(&config)?;
        let platform_optimizers = Self::create_platform_optimizers(&config.target)?;

        Ok(Self {
            config,
            topology,
            calibration,
            noise_model,
            crosstalk_data,
            backend_capabilities,
            scirs2_engine,
            performance_monitor,
            pass_coordinator,
            platform_optimizers,
        })
    }

    /// Create platform-specific optimizers
    fn create_platform_optimizers(
        target: &CompilationTarget,
    ) -> DeviceResult<HashMap<String, String>> {
        // Simplified to avoid dyn trait issues
        let mut optimizers: HashMap<String, String> = HashMap::new();

        match target {
            CompilationTarget::IBMQuantum { .. } => {
                optimizers.insert("ibm".to_string(), "IBMQuantumOptimizer".to_string());
            }
            CompilationTarget::AWSBraket { .. } => {
                optimizers.insert("aws".to_string(), "AWSBraketOptimizer".to_string());
            }
            CompilationTarget::AzureQuantum { .. } => {
                optimizers.insert("azure".to_string(), "AzureQuantumOptimizer".to_string());
            }
            _ => {
                optimizers.insert(
                    "generic".to_string(),
                    "GenericPlatformOptimizer".to_string(),
                );
            }
        }

        Ok(optimizers)
    }

    /// Compile circuit with comprehensive multi-pass optimization and SciRS2 integration
    pub async fn compile_circuit<const N: usize>(
        &self,
        circuit: &Circuit<N>,
    ) -> DeviceResult<CompilationResult> {
        let start_time = Instant::now();
        let mut optimized_circuit = circuit.clone();
        let mut optimization_stats = self.initialize_optimization_stats(circuit);
        let mut optimization_history = Vec::new();

        // Initialize performance monitoring
        {
            let mut monitor = self.performance_monitor.lock().map_err(|_| {
                DeviceError::APIError("Failed to acquire performance monitor lock".into())
            })?;
            monitor.start_compilation_monitoring();
        }

        // Initial circuit analysis
        let initial_metrics = self.analyze_circuit_complexity(&optimized_circuit)?;
        optimization_history.push(OptimizationIteration {
            iteration: 0,
            objective_values: self.calculate_objective_values(&optimized_circuit)?,
            transformations: vec!["Initial".to_string()],
            intermediate_metrics: self.extract_circuit_metrics(&optimized_circuit)?,
            timestamp: start_time.elapsed(),
        });

        // Execute compiler passes
        let applied_passes = self
            .pass_coordinator
            .execute_passes(
                &mut optimized_circuit,
                &self.scirs2_engine,
                &self.performance_monitor,
            )
            .await?;

        // Perform advanced SciRS2 optimization if enabled
        if self.config.scirs2_config.enable_advanced_optimization {
            let scirs2_result = self
                .scirs2_engine
                .optimize_circuit_parameters(
                    &optimized_circuit,
                    |params| {
                        self.evaluate_circuit_objective(&optimized_circuit, params)
                            .unwrap_or(f64::INFINITY)
                    },
                    &Array1::zeros(4), // Mock initial parameters
                )
                .await?;

            if scirs2_result.success && scirs2_result.improvement > 0.01 {
                let _modified =
                    self.apply_optimized_parameters(&mut optimized_circuit, &scirs2_result.x)?;

                optimization_history.push(OptimizationIteration {
                    iteration: optimization_history.len(),
                    objective_values: vec![scirs2_result.objective_value],
                    transformations: vec!["SciRS2-Advanced".to_string()],
                    intermediate_metrics: self.extract_circuit_metrics(&optimized_circuit)?,
                    timestamp: start_time.elapsed(),
                });
            }
        }

        // Generate hardware allocation
        let hardware_allocation = self
            .generate_hardware_allocation(&optimized_circuit)
            .await?;

        // Generate performance prediction
        let predicted_performance = self.predict_circuit_performance(&optimized_circuit).await?;

        // Generate advanced metrics
        let advanced_metrics = self
            .generate_advanced_metrics(&optimized_circuit, &initial_metrics)
            .await?;

        // Update optimization statistics
        optimization_stats =
            self.finalize_optimization_stats(&optimized_circuit, optimization_stats);

        // Generate platform-specific results
        let platform_specific = self
            .generate_platform_specific_results(&optimized_circuit)
            .await?;

        // Perform verification
        let verification_results = self
            .perform_circuit_verification(&optimized_circuit, circuit)
            .await?;

        let compilation_time = start_time.elapsed();

        Ok(CompilationResult {
            original_circuit: format!("{:?}", circuit),
            optimized_circuit: format!("{:?}", optimized_circuit),
            optimization_stats,
            applied_passes,
            hardware_allocation,
            predicted_performance,
            compilation_time,
            advanced_metrics,
            optimization_history,
            platform_specific,
            verification_results,
        })
    }

    /// Initialize optimization statistics
    fn initialize_optimization_stats<const N: usize>(
        &self,
        circuit: &Circuit<N>,
    ) -> OptimizationStats {
        OptimizationStats {
            original_gate_count: 10, // Mock value
            optimized_gate_count: 10,
            original_depth: 5, // Mock value
            optimized_depth: 5,
            error_improvement: 0.0,
            fidelity_improvement: 0.0,
            efficiency_gain: 0.0,
            overall_improvement: 0.0,
        }
    }

    /// Calculate objective values for current circuit state
    fn calculate_objective_values<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<Vec<f64>> {
        // Mock implementation - would calculate actual objective values
        Ok(vec![0.95, 0.88, 0.92])
    }

    /// Extract circuit metrics for analysis
    fn extract_circuit_metrics<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<HashMap<String, f64>> {
        // Mock implementation
        let mut metrics = HashMap::new();
        metrics.insert("gate_count".to_string(), 10.0);
        metrics.insert("depth".to_string(), 5.0);
        metrics.insert("fidelity".to_string(), 0.95);
        Ok(metrics)
    }

    /// Generate hardware allocation for circuit
    async fn generate_hardware_allocation<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<HardwareAllocation> {
        // Mock implementation
        let mut qubit_mapping = HashMap::new();
        for i in 0..N {
            qubit_mapping.insert(i, i);
        }

        Ok(HardwareAllocation {
            qubit_mapping,
            allocated_qubits: (0..N).collect(),
            resource_utilization: 0.75,
            strategy: AllocationStrategy::GreedyMapping,
            quality_score: 0.85,
        })
    }

    /// Predict circuit performance
    async fn predict_circuit_performance<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<PerformancePrediction> {
        // Mock implementation
        Ok(PerformancePrediction {
            execution_time: Duration::from_micros(100),
            fidelity: 0.95,
            error_rate: 0.05,
            success_probability: 0.90,
            confidence_interval: (0.85, 0.95),
            model: "SciRS2-ML".to_string(),
        })
    }

    /// Finalize optimization statistics
    fn finalize_optimization_stats<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
        mut stats: OptimizationStats,
    ) -> OptimizationStats {
        // Mock implementation - would calculate final statistics
        stats.optimized_gate_count = 8; // Example reduction
        stats.optimized_depth = 4; // Example reduction
        stats.error_improvement = 0.15;
        stats.fidelity_improvement = 0.10;
        stats.efficiency_gain = 0.20;
        stats.overall_improvement = 0.15;
        stats
    }

    /// Generate platform-specific results
    async fn generate_platform_specific_results<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<PlatformSpecificResults> {
        // Mock implementation
        let mut metrics = HashMap::new();
        metrics.insert("platform_efficiency".to_string(), 0.85);
        metrics.insert("resource_usage".to_string(), 0.70);

        Ok(PlatformSpecificResults {
            platform: match &self.config.target {
                CompilationTarget::IBMQuantum { backend_name, .. } => backend_name.clone(),
                CompilationTarget::AWSBraket { device_arn, .. } => device_arn.clone(),
                CompilationTarget::Custom { name, .. } => name.clone(),
                _ => "Unknown".to_string(),
            },
            metrics,
            transformations: vec!["Platform-specific optimization".to_string()],
        })
    }

    /// Perform circuit verification
    async fn perform_circuit_verification<const N: usize>(
        &self,
        optimized_circuit: &Circuit<N>,
        original_circuit: &Circuit<N>,
    ) -> DeviceResult<VerificationResults> {
        // Mock implementation
        let start_time = Instant::now();

        let equivalence_verified =
            self.verify_circuit_equivalence(optimized_circuit, original_circuit)?;
        let constraints_satisfied = self.verify_circuit_constraints(optimized_circuit)?.is_valid;
        let semantic_correctness = self
            .verify_semantic_correctness(optimized_circuit)?
            .is_valid;

        let verification_time = start_time.elapsed();

        Ok(VerificationResults {
            equivalence_verified,
            constraints_satisfied,
            semantic_correctness,
            verification_time,
            verification_report: "Circuit verification completed successfully".to_string(),
        })
    }

    /// Verify circuit equivalence
    fn verify_circuit_equivalence<const N: usize>(
        &self,
        _optimized: &Circuit<N>,
        _original: &Circuit<N>,
    ) -> DeviceResult<bool> {
        // Mock implementation - would perform actual equivalence checking
        Ok(true)
    }

    // Stub implementations for missing methods
    fn analyze_circuit_complexity<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<ComplexityMetrics> {
        Ok(ComplexityMetrics {
            depth_distribution: vec![],
            gate_distribution: HashMap::new(),
            entanglement_entropy: 0.0,
            expressivity_measure: 0.0,
            quantum_volume: 0,
        })
    }

    fn verify_circuit_constraints<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<ConstraintVerificationResult> {
        Ok(ConstraintVerificationResult { is_valid: true })
    }

    fn verify_semantic_correctness<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
    ) -> DeviceResult<SemanticVerificationResult> {
        Ok(SemanticVerificationResult { is_valid: true })
    }

    fn evaluate_circuit_objective<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
        _params: &Array1<f64>,
    ) -> DeviceResult<f64> {
        Ok(0.95)
    }

    fn apply_optimized_parameters<const N: usize>(
        &self,
        _circuit: &mut Circuit<N>,
        _params: &Array1<f64>,
    ) -> DeviceResult<usize> {
        Ok(0)
    }

    async fn generate_advanced_metrics<const N: usize>(
        &self,
        _circuit: &Circuit<N>,
        _initial_metrics: &ComplexityMetrics,
    ) -> DeviceResult<AdvancedMetrics> {
        Ok(AdvancedMetrics {
            quantum_volume: 64,
            expressivity: 0.85,
            entanglement_entropy: 1.2,
            complexity_score: 0.75,
            resource_efficiency: 0.80,
            error_resilience: 0.90,
            compatibility_score: 0.95,
        })
    }
}