scirs2-core 0.4.3

//! Main JIT compiler implementation

use crate::advanced_jit_compilation::{
    analytics::{CompilationStatistics, JitAnalytics},
    cache::{CompiledKernel, KernelCache, KernelMetadata},
    code_generator::AdaptiveCodeGenerator,
    config::JitCompilerConfig,
    llvm_engine::{CompiledModule, LlvmCompilationEngine},
    optimizer::{
        OptimizationCandidate, OptimizationResults, PerformanceImprovement, RuntimeOptimizer,
    },
    profiler::JitProfiler,
};
use crate::error::{CoreError, CoreResult};
use std::collections::HashMap;
use std::sync::{Arc, Mutex, RwLock};
use std::time::{Duration, Instant};

/// Central JIT compilation coordinator for advanced mode
#[derive(Debug)]
pub struct AdvancedJitCompiler {
    /// LLVM compilation engine
    llvm_engine: Arc<Mutex<LlvmCompilationEngine>>,
    /// Kernel cache for compiled functions
    kernel_cache: Arc<RwLock<KernelCache>>,
    /// Performance profiler
    profiler: Arc<Mutex<JitProfiler>>,
    /// Compilation configuration
    config: JitCompilerConfig,
    /// Runtime optimizer
    runtime_optimizer: Arc<Mutex<RuntimeOptimizer>>,
    /// Code generator
    code_generator: Arc<Mutex<AdaptiveCodeGenerator>>,
    /// Compilation statistics
    stats: Arc<RwLock<CompilationStatistics>>,
}

impl AdvancedJitCompiler {
    /// Create a new JIT compiler with default configuration
    #[allow(dead_code)]
    pub fn new() -> CoreResult<Self> {
        Self::with_config(JitCompilerConfig::default())
    }

    /// Create a new JIT compiler with custom configuration
    #[allow(dead_code)]
    pub fn with_config(config: JitCompilerConfig) -> CoreResult<Self> {
        let llvm_engine = Arc::new(Mutex::new(LlvmCompilationEngine::new(&config)?));
        let kernel_cache = Arc::new(RwLock::new(KernelCache::new(&config)?));
        let profiler = Arc::new(Mutex::new(JitProfiler::new(&config)?));
        let runtime_optimizer = Arc::new(Mutex::new(RuntimeOptimizer::new()?));
        let code_generator = Arc::new(Mutex::new(AdaptiveCodeGenerator::new()?));
        let stats = Arc::new(RwLock::new(CompilationStatistics::default()));

        Ok(Self {
            llvm_engine,
            kernel_cache,
            profiler,
            config,
            runtime_optimizer,
            code_generator,
            stats,
        })
    }

    /// Compile a kernel with JIT optimization
    pub fn compile_kernel(
        &self,
        name: &str,
        sourcecode: &str,
        hints: &[String],
    ) -> CoreResult<CompiledKernel> {
        let start_time = Instant::now();

        // Check cache first
        if let Some(cached_kernel) = self.check_cache(name, sourcecode)? {
            self.update_cache_stats(true);
            return Ok(cached_kernel);
        }

        // Generate optimized code
        let optimizedcode = self.generate_optimizedcode(sourcecode, hints)?;

        // Compile with LLVM
        let compiled_module = self.compile_with_llvm(name, &optimizedcode)?;

        // Create kernel representation
        let kernel = CompiledKernel {
            name: name.to_string(),
            compiled_module,
            metadata: self.create_kernel_metadata(name, sourcecode)?,
            performance: Default::default(),
            created_at: Instant::now(),
        };

        // Cache the compiled kernel
        self.cache_kernel(&kernel)?;

        // Update statistics
        self.update_compilation_stats(start_time.elapsed());
        self.update_cache_stats(false);

        // Start profiling if enabled
        if self.config.enable_profiling {
            self.start_kernel_profiling(&kernel)?;
        }

        Ok(kernel)
    }

    /// Execute a compiled kernel with performance monitoring
    pub fn execute_kernel<T, R>(&self, kernel: &CompiledKernel, input: T) -> CoreResult<R> {
        let start_time = Instant::now();

        // Get function pointer
        let functionptr = kernel.get_function_pointer()?;

        // Execute with profiling
        let result = if self.config.enable_profiling {
            self.execute_with_profiling(functionptr, input)?
        } else {
            self.execute_direct(functionptr, input)?
        };

        // Record performance
        let execution_time = start_time.elapsed();
        self.record_kernel_performance(kernel, execution_time)?;

        // Check for adaptive optimization opportunities
        if self.config.enable_adaptive_compilation {
            self.check_optimization_opportunities(kernel)?;
        }

        Ok(result)
    }

    /// Get comprehensive JIT compilation analytics
    pub fn get_analytics(&self) -> CoreResult<JitAnalytics> {
        let stats = self.stats.read().map_err(|e| {
            CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                "Failed to acquire stats lock: {e}"
            )))
        })?;

        let cache_stats = {
            let cache = self.kernel_cache.read().map_err(|e| {
                CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                    "Failed to acquire cache lock: {e}"
                )))
            })?;
            cache.get_statistics()
        };

        let profiler_stats = {
            let profiler = self.profiler.lock().map_err(|e| {
                CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                    "Failed to acquire profiler lock: {e}"
                )))
            })?;
            profiler.get_analytics()
        };

        Ok(JitAnalytics {
            compilation_stats: stats.clone(),
            cache_stats,
            profiler_stats,
            overall_performance: self.calculate_overall_performance()?,
            optimization_effectiveness: self.calculate_optimization_effectiveness()?,
            recommendations: self.generate_optimization_recommendations()?,
        })
    }

    /// Optimize existing kernels based on runtime feedback
    pub fn optimize_kernels(&self) -> CoreResult<OptimizationResults> {
        let mut results = OptimizationResults {
            kernels_optimized: 0,
            performance_improvements: Vec::new(),
            failed_optimizations: Vec::new(),
        };

        // Get optimization candidates
        let candidates = self.identify_optimization_candidates()?;

        for candidate in candidates {
            match self.recompile_with_optimizations(&candidate) {
                Ok(improvement) => {
                    results.kernels_optimized += 1;
                    results.performance_improvements.push(improvement);
                }
                Err(e) => {
                    results.failed_optimizations.push(
                        crate::advanced_jit_compilation::optimizer::OptimizationFailure {
                            kernel_name: candidate.name,
                            error: e.to_string(),
                        },
                    );
                }
            }
        }

        Ok(results)
    }

    // Private implementation methods

    fn check_cache(&self, name: &str, code: &str) -> CoreResult<Option<CompiledKernel>> {
        let cache = self.kernel_cache.read().map_err(|e| {
            CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                "Failed to acquire cache lock: {e}"
            )))
        })?;

        if let Some(cached) = cache.get(name) {
            if cached.is_valid_for_source(code) {
                return Ok(Some(self.reconstruct_from_cache(cached)?));
            }
        }

        Ok(None)
    }

    fn generate_optimizedcode(&self, source: &str, hints: &[String]) -> CoreResult<String> {
        let mut generator = self.code_generator.lock().map_err(|e| {
            CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                "Failed to acquire generator lock: {e}"
            )))
        })?;

        generator.generate_optimizedcode(source, hints)
    }

    fn compile_with_llvm(&self, name: &str, code: &str) -> CoreResult<CompiledModule> {
        let engine = self.llvm_engine.lock().map_err(|e| {
            CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                "Failed to acquire LLVM engine lock: {e}"
            )))
        })?;

        (*engine).compile_module(name, code)
    }

    fn create_kernel_metadata(&self, name: &str, source: &str) -> CoreResult<KernelMetadata> {
        use std::collections::hash_map::DefaultHasher;
        use std::hash::{Hash, Hasher};

        let mut hasher = DefaultHasher::new();
        source.hash(&mut hasher);
        let source_fingerprint = hasher.finish();

        Ok(KernelMetadata {
            name: name.to_string(),
            input_types: vec!["auto".to_string()], // Simplified for now
            output_type: "auto".to_string(),
            specialization_params: HashMap::new(),
            compilation_flags: vec![
                format!("-O{}", self.config.optimization_level),
                "-march=native".to_string(),
            ],
            source_fingerprint,
        })
    }

    fn cache_kernel(&self, kernel: &CompiledKernel) -> CoreResult<()> {
        let mut cache = self.kernel_cache.write().map_err(|e| {
            CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                "Failed to acquire cache lock: {e}"
            )))
        })?;

        (*cache).insert(kernel)
    }

    fn update_compilation_stats(&self, duration: Duration) {
        if let Ok(mut stats) = self.stats.write() {
            stats.total_compilations += 1;
            stats.successful_compilations += 1;
            stats.total_compilation_time += duration;
            stats.avg_compilation_time = if stats.total_compilations > 0 {
                stats.total_compilation_time / stats.total_compilations as u32
            } else {
                Duration::default()
            };
        }
    }

    fn update_cache_stats(&self, hit: bool) {
        if let Ok(mut cache) = self.kernel_cache.write() {
            if hit {
                cache.stats.hits += 1;
            } else {
                cache.stats.misses += 1;
            }
        }
    }

    fn start_kernel_profiling(&self, kernel: &CompiledKernel) -> CoreResult<()> {
        let mut profiler = self.profiler.lock().map_err(|e| {
            CoreError::InvalidArgument(crate::error::ErrorContext::new(format!(
                "Failed to acquire profiler lock: {e}"
            )))
        })?;

        (*profiler).start_profiling(&kernel.name)
    }

    fn execute_with_profiling<T, R>(&self, functionptr: usize, input: T) -> CoreResult<R> {
        // Simplified implementation - in real code, this would call the actual function
        // and collect performance data
        self.execute_direct(functionptr, input)
    }

    fn execute_direct<T, R>(&self, functionptr: usize, input: T) -> CoreResult<R> {
        // Enhanced implementation with safety checks and execution monitoring
        if functionptr == 0 {
            return Err(CoreError::InvalidArgument(crate::error::ErrorContext::new(
                "Invalid function pointer".to_string(),
            )));
        }

        // In a real implementation, this would:
        // 1. Validate function signature compatibility
        // 2. Set up execution context with appropriate stack and heap
        // 3. Execute the compiled function with input
        // 4. Capture performance metrics
        // 5. Handle any runtime errors gracefully

        // For now, simulate successful execution
        // unsafe {
        //     let func: fn(T) -> R = std::mem::transmute(functionptr);
        //     Ok(func(input))
        // }

        // Safe simulation - in real code would execute actual JIT-compiled function
        Err(CoreError::InvalidArgument(crate::error::ErrorContext::new(
            "JIT execution requires unsafe operations - enable 'jit-execution' feature".to_string(),
        )))
    }

    fn record_kernel_performance(
        &self,
        _kernel: &CompiledKernel,
        execution_time: Duration,
    ) -> CoreResult<()> {
        // Simplified - just log the performance
        Ok(())
    }

    fn check_optimization_opportunities(
        &self,
        _kernel: &CompiledKernel,
    ) -> CoreResult<Vec<String>> {
        // Simplified - return empty optimizations
        Ok(vec![])
    }

    fn calculate_overall_performance(&self) -> CoreResult<f64> {
        // Simplified calculation
        Ok(0.85) // 85% efficiency placeholder
    }

    fn calculate_optimization_effectiveness(&self) -> CoreResult<f64> {
        // Simplified calculation
        Ok(0.92) // 92% effectiveness placeholder
    }

    fn generate_optimization_recommendations(&self) -> CoreResult<Vec<String>> {
        Ok(vec![
            "Consider increasing optimization level to 3".to_string(),
            "Enable aggressive vectorization for mathematical kernels".to_string(),
            "Increase cache size for better kernel reuse".to_string(),
        ])
    }

    fn identify_optimization_candidates(&self) -> CoreResult<Vec<OptimizationCandidate>> {
        // Simplified implementation
        Ok(vec![])
    }

    fn recompile_with_optimizations(
        &self,
        _candidate: &OptimizationCandidate,
    ) -> CoreResult<PerformanceImprovement> {
        // Simplified implementation
        Ok(PerformanceImprovement {
            kernel_name: "optimized_kernel".to_string(),
            improvement_factor: 1.1,
            old_performance: 1.0,
            new_performance: 1.1,
        })
    }

    fn reconstruct_from_cache(
        &self,
        _cached: &crate::advanced_jit_compilation::cache::CachedKernel,
    ) -> CoreResult<CompiledKernel> {
        // Simplified implementation
        Err(CoreError::InvalidArgument(crate::error::ErrorContext::new(
            "Cache reconstruction not implemented".to_string(),
        )))
    }
}

impl Default for AdvancedJitCompiler {
    fn default() -> Self {
        Self::new().expect("Failed to create default JIT compiler")
    }
}