amberjs 1.16.1

// Stage 92 Phase 2: 极致内存优化集成引擎
//
// 整合 DMA、内存映射、智能预取和 GC 优化，实现极致内存性能

use anyhow::Result;
use std::alloc::GlobalAlloc;
use std::ptr::NonNull;
use std::sync::Arc;
use std::time::{Duration, Instant};

use crate::memory::{
    AccessPattern, DmaConfig, EnhancedGcOptimizer, EnhancedZeroCopy, GcConfig, MmapConfig,
    PrefetchConfig, PrefetchStrategy, SmartPrefetcher,
};

/// 线程安全的 NonNull 指针包装器
#[derive(Debug, Copy, Clone, PartialEq, Eq)]
pub struct SendPtr(pub NonNull<u8>);

unsafe impl Send for SendPtr {}
unsafe impl Sync for SendPtr {}

impl std::ops::Deref for SendPtr {
    type Target = NonNull<u8>;
    fn deref(&self) -> &Self::Target {
        &self.0
    }
}

/// Phase 2 内存引擎配置
#[derive(Debug, Clone)]
pub struct Phase2MemoryConfig {
    /// DMA 配置
    pub dma_config: DmaConfig,
    /// 内存映射配置
    pub mmap_config: MmapConfig,
    /// 预取配置
    pub prefetch_config: PrefetchConfig,
    /// GC 配置
    pub gc_config: GcConfig,
    /// 预取策略
    pub prefetch_strategy: PrefetchStrategy,
    /// 启用 AI 优化
    pub enable_ai_optimization: bool,
    /// 内存压缩阈值
    pub compression_threshold: usize,
}
impl Default for Phase2MemoryConfig {
    fn default() -> Self {
        Self {
            dma_config: DmaConfig::default(),
            mmap_config: MmapConfig::default(),
            prefetch_config: PrefetchConfig::default(),
            gc_config: GcConfig::default(),
            prefetch_strategy: PrefetchStrategy::default(),
            enable_ai_optimization: true,
            compression_threshold: 1024 * 1024, // 1MB
        }
    }
}
/// Phase 2 内存引擎
#[derive(Debug)]
pub struct Phase2MemoryEngine {
    /// 配置
    config: Phase2MemoryConfig,
    /// 零拷贝系统
    zero_copy: Arc<EnhancedZeroCopy>,
    /// 智能预取器
    prefetcher: Arc<SmartPrefetcher>,
    /// GC 优化器
    gc_optimizer: Arc<EnhancedGcOptimizer>,
    /// 性能统计
    stats: Arc<Phase2MemoryStats>,
    /// 启动时间
    started_at: Instant,
}
/// Phase 2 内存统计
#[derive(Debug, Default)]
pub struct Phase2MemoryStats {
    pub total_allocations: std::sync::atomic::AtomicUsize,
    pub total_deallocations: std::sync::atomic::AtomicUsize,
    pub total_bytes_allocated: std::sync::atomic::AtomicUsize,
    pub total_bytes_freed: std::sync::atomic::AtomicUsize,
    pub zero_copy_operations: std::sync::atomic::AtomicUsize,
    pub dma_operations: std::sync::atomic::AtomicUsize,
    pub mmap_operations: std::sync::atomic::AtomicUsize,
    pub prefetch_operations: std::sync::atomic::AtomicUsize,
    pub gc_collections: std::sync::atomic::AtomicUsize,
    pub bytes_saved: std::sync::atomic::AtomicUsize,
    pub time_saved_ms: std::sync::atomic::AtomicUsize,
    pub memory_reduction_percent: std::sync::atomic::AtomicUsize,
}
impl Phase2MemoryEngine {
    /// 创建 Phase 2 内存引擎
    pub fn new(config: Phase2MemoryConfig) -> Self {
        let zero_copy = Arc::new(EnhancedZeroCopy::new(
            config.dma_config.clone(),
            config.mmap_config.clone(),
            config.prefetch_config.clone(),
        ));
        let prefetcher = Arc::new(SmartPrefetcher::new(
            zero_copy.clone(),
            config.prefetch_strategy.clone(),
        ));
        let gc_optimizer = Arc::new(EnhancedGcOptimizer::new(config.gc_config.clone()));
        // 启用预测性 GC
        gc_optimizer.enable_predictive_gc();
        Self {
            config,
            zero_copy,
            prefetcher,
            gc_optimizer,
            stats: Arc::new(Phase2MemoryStats::default()),
            started_at: Instant::now(),
        }
    }
    /// 使用默认配置创建
    pub fn default() -> Self {
        Self::new(Phase2MemoryConfig::default())
    }
    /// 分配内存
    pub async fn allocate(&self, size: usize) -> Result<SendPtr, &'static str> {
        // 记录分配
        self.stats
            .total_allocations
            .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
        self.stats
            .total_bytes_allocated
            .fetch_add(size, std::sync::atomic::Ordering::Relaxed);
        // 检查是否应该使用 DMA
        let result: _ = if size >= self.config.dma_config.dma_threshold {
            // 使用 DMA 分配
            let buffer: _ = self
                .zero_copy
                .allocate_dma(size)
                .await
                .map_err(|_| "DMA allocation failed")?;
            self.stats
                .dma_operations
                .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
            Ok(SendPtr(buffer.ptr))
        } else {
            // 使用标准分配
            let layout: _ =
                std::alloc::Layout::from_size_align(size, std::mem::align_of::<usize>())
                    .map_err(|_| "Invalid layout")?;
            unsafe {
                let ptr: _ = std::alloc::System.alloc(layout);
                if ptr.is_null() {
                    Err("Allocation failed")
                } else {
                    Ok(SendPtr(NonNull::new_unchecked(ptr)))
                }
            }
        };
        // 记录到 GC 优化器
        self.gc_optimizer.record_allocation(size).await;
        // 如果启用 AI 优化，记录访问
        if self.config.enable_ai_optimization {
            let addr: _ = match &result {
                Ok(ptr) => ptr.as_ptr() as usize,
                Err(_) => 0,
            };
            if addr > 0 {
                self.prefetcher.record_access(addr, size).await;
            }
        }
        result
    }
    /// 释放内存
    pub async fn deallocate(&self, ptr: SendPtr, size: usize) -> Result<(), &'static str> {
        // 记录释放
        self.stats
            .total_deallocations
            .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
        self.stats
            .total_bytes_freed
            .fetch_add(size, std::sync::atomic::Ordering::Relaxed);
        // 记录到 GC 优化器
        self.gc_optimizer.record_deallocation(size).await;
        // 对于 DMA 缓冲区，返回到池中
        if size >= self.config.dma_config.dma_threshold {
            // 注意：这里需要 DmaBuffer 对象，在实际实现中需要改进
            // self.zero_copy.deallocate_dma(buffer).await.map_err(|_| "DMA deallocation failed")?;
        } else {
            // 标准释放
            unsafe {
                let layout: _ = std::alloc::Layout::from_size_align_unchecked(
                    size,
                    std::mem::align_of::<usize>(),
                );
                std::alloc::System.dealloc(ptr.as_ptr(), layout);
            }
        }
        Ok(())
    }
    /// 内存映射文件
    pub async fn mmap_file(
        &self,
        path: &str,
        size: usize,
    ) -> Result<Arc<memmap2::Mmap>, anyhow::Error> {
        self.stats
            .mmap_operations
            .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
        // 使用零拷贝系统进行内存映射
        let mmap: _ = self.zero_copy.mmap_file(path, size).await?;
        Ok(mmap)
    }
    /// 智能预取
    pub async fn smart_prefetch(
        &self,
        addr: SendPtr,
        size: usize,
        pattern: AccessPattern,
    ) -> Result<()> {
        self.stats
            .prefetch_operations
            .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
        // 使用零拷贝系统进行预取
        self.zero_copy
            .predictive_prefetch(addr, size, pattern)
            .await?;
        Ok(())
    }
    /// 执行零拷贝数据传输
    pub async fn zero_copy_transfer(&self, src: SendPtr, dst: SendPtr, size: usize) -> Result<()> {
        self.stats
            .zero_copy_operations
            .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
        self.stats
            .bytes_saved
            .fetch_add(size, std::sync::atomic::Ordering::Relaxed);
        self.zero_copy.zero_copy_transfer(src, dst, size).await?;
        Ok(())
    }
    /// 强制执行 GC
    pub async fn force_gc(&self) -> Result<()> {
        self.stats
            .gc_collections
            .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
        // 模拟 GC 执行
        self.gc_optimizer
            .trigger_gc(crate::memory::GcTriggerDecision {
                should_trigger: true,
                strategy: crate::memory::GcStrategy::Emergency,
                reason: "Manual GC trigger".to_string(),
                confidence: 1.0,
            })
            .await;
        Ok(())
    }
    /// 获取内存使用统计
    pub async fn get_memory_stats(&self) -> Phase2MemoryStatsSnapshot {
        let prefetch_stats: _ = self.zero_copy.get_prefetch_stats().await;
        let gc_metrics: _ = self.gc_optimizer.get_metrics().await;
        Phase2MemoryStatsSnapshot {
            uptime: self.started_at.elapsed(),
            total_allocations: self
                .stats
                .total_allocations
                .load(std::sync::atomic::Ordering::Relaxed),
            total_deallocations: self
                .stats
                .total_deallocations
                .load(std::sync::atomic::Ordering::Relaxed),
            total_bytes_allocated: self
                .stats
                .total_bytes_allocated
                .load(std::sync::atomic::Ordering::Relaxed),
            total_bytes_freed: self
                .stats
                .total_bytes_freed
                .load(std::sync::atomic::Ordering::Relaxed),
            current_memory_usage: self
                .stats
                .total_bytes_allocated
                .load(std::sync::atomic::Ordering::Relaxed)
                .saturating_sub(
                    self.stats
                        .total_bytes_freed
                        .load(std::sync::atomic::Ordering::Relaxed),
                ),
            zero_copy_operations: self
                .stats
                .zero_copy_operations
                .load(std::sync::atomic::Ordering::Relaxed),
            dma_operations: self
                .stats
                .dma_operations
                .load(std::sync::atomic::Ordering::Relaxed),
            mmap_operations: self
                .stats
                .mmap_operations
                .load(std::sync::atomic::Ordering::Relaxed),
            prefetch_operations: self
                .stats
                .prefetch_operations
                .load(std::sync::atomic::Ordering::Relaxed),
            gc_collections: self
                .stats
                .gc_collections
                .load(std::sync::atomic::Ordering::Relaxed),
            bytes_saved: self
                .stats
                .bytes_saved
                .load(std::sync::atomic::Ordering::Relaxed),
            time_saved_ms: self
                .stats
                .time_saved_ms
                .load(std::sync::atomic::Ordering::Relaxed),
            gc_metrics,
            prefetch_stats,
        }
    }
    /// 获取内存效率指标
    pub async fn get_efficiency_metrics(&self) -> Phase2EfficiencyMetrics {
        let stats: _ = self.get_memory_stats().await;
        let allocation_efficiency: _ = if stats.total_bytes_allocated > 0 {
            stats.total_bytes_freed as f64 / stats.total_bytes_allocated as f64
        } else {
            0.0
        };
        let zero_copy_ratio: _ = if stats.total_allocations > 0 {
            stats.zero_copy_operations as f64 / stats.total_allocations as f64
        } else {
            0.0
        };
        let memory_reduction: _ = if stats.total_bytes_allocated > 0 {
            stats.bytes_saved as f64 / stats.total_bytes_allocated as f64
        } else {
            0.0
        };
        Phase2EfficiencyMetrics {
            allocation_efficiency,
            zero_copy_ratio,
            memory_reduction_percent: memory_reduction * 100.0,
            gc_efficiency: stats.gc_metrics.collection_rate(),
            prefetch_success_rate: stats.prefetch_stats.success_rate(),
        }
    }
    /// 清理资源
    pub async fn cleanup(&self) {
        // 清理预取器过期任务
        self.prefetcher.cleanup_expired_tasks().await;
        // 强制执行一次 GC
        let _: _ = self.force_gc().await;
    }
}
/// Phase 2 内存统计快照
#[derive(Debug, Clone)]
pub struct Phase2MemoryStatsSnapshot {
    pub uptime: Duration,
    pub total_allocations: usize,
    pub total_deallocations: usize,
    pub total_bytes_allocated: usize,
    pub total_bytes_freed: usize,
    pub current_memory_usage: usize,
    pub zero_copy_operations: usize,
    pub dma_operations: usize,
    pub mmap_operations: usize,
    pub prefetch_operations: usize,
    pub gc_collections: usize,
    pub bytes_saved: usize,
    pub time_saved_ms: usize,
    pub gc_metrics: crate::memory::GcMetricsSnapshot,
    pub prefetch_stats: crate::memory::PrefetchStatsSnapshot,
}
/// Phase 2 效率指标
#[derive(Debug, Clone)]
pub struct Phase2EfficiencyMetrics {
    pub allocation_efficiency: f64,
    pub zero_copy_ratio: f64,
    pub memory_reduction_percent: f64,
    pub gc_efficiency: f64,
    pub prefetch_success_rate: f64,
}
impl Phase2EfficiencyMetrics {
    pub fn overall_score(&self) -> f64 {
        // 计算综合性能得分 (0-100)
        let allocation_score: _ = self.allocation_efficiency * 20.0;
        let zero_copy_score: _ = self.zero_copy_ratio * 25.0;
        let memory_score: _ = (self.memory_reduction_percent / 100.0) * 25.0;
        let gc_score: _ = (self.gc_efficiency / 1_000_000.0).min(1.0) * 15.0;
        let prefetch_score: _ = self.prefetch_success_rate * 15.0;
        allocation_score + zero_copy_score + memory_score + gc_score + prefetch_score
    }
    pub fn performance_tier(&self) -> &'static str {
        let score: _ = self.overall_score();
        if score >= 90.0 {
            "S - 极致性能"
        } else if score >= 80.0 {
            "A - 优秀性能"
        } else if score >= 70.0 {
            "B - 良好性能"
        } else if score >= 60.0 {
            "C - 一般性能"
        } else {
            "D - 需要优化"
        }
    }
}
#[cfg(test)]
mod tests {
    use super::*;

    #[tokio::test]
    async fn test_phase2_memory_engine_creation() {
        let engine: _ = Phase2MemoryEngine::default();
        assert!(engine.config.enable_ai_optimization);
    }
    #[tokio::test]
    async fn test_memory_allocation() {
        let engine: _ = Phase2MemoryEngine::default();
        // 分配小内存
        let ptr: _ = engine.allocate(1024).await.unwrap();
        // 释放内存
        engine.deallocate(ptr, 1024).await.unwrap();
    }
    #[tokio::test]
    async fn test_zero_copy_transfer() {
        let engine: _ = Phase2MemoryEngine::default();
        // 分配两个缓冲区
        let src: _ = engine.allocate(1024).await.unwrap();
        let dst: _ = engine.allocate(1024).await.unwrap();
        // 执行零拷贝传输
        engine.zero_copy_transfer(src, dst, 1024).await.unwrap();
        // 清理
        engine.deallocate(src, 1024).await.unwrap();
        engine.deallocate(dst, 1024).await.unwrap();
    }
    #[tokio::test]
    async fn test_memory_stats() {
        let engine: _ = Phase2MemoryEngine::default();
        // 执行一些操作
        engine.allocate(1024).await.unwrap();
        engine.force_gc().await.unwrap();
        let stats: _ = engine.get_memory_stats().await;
        assert!(stats.total_allocations > 0);
    }
    #[tokio::test]
    async fn test_efficiency_metrics() {
        let engine: _ = Phase2MemoryEngine::default();
        let metrics: _ = engine.get_efficiency_metrics().await;
        assert!(metrics.allocation_efficiency >= 0.0);
        assert!(metrics.zero_copy_ratio >= 0.0);
        assert!(metrics.overall_score() >= 0.0);
    }
}