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v0.6.3

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@HelloAIXIAOJI HelloAIXIAOJI released this 02 Aug 18:43
· 652 commits to master since this release
v0.6.3
07c855a

[v0.6.3] - 2025-08-02

🚀 Simple Type Fast Path Optimization

Core Improvements

  • Smart Memory Allocation: Implemented type-based intelligent allocation strategy, using fast paths for simple types
  • Performance Optimization: Optimized memory allocation for simple types like int, float, bool, and long
  • Safety Guarantee: Maintained full security checks for complex types to ensure memory safety

Technical Implementation

🎯 Fast Allocation for Simple Types
/// 🚀 v0.6.3 Fast Allocation for Simple Types - Skips complex security checks
fn allocate_simple_type_fast(value: Value) -> Result<(usize, u64), String> {
    let mut manager = MEMORY_MANAGER.write().unwrap();

    // Inline size calculation to avoid function call overhead
    let size = match &value {
        Value::Int(_) => std::mem::size_of::<i32>(),
        Value::Long(_) => std::mem::size_of::<i64>(),
        Value::Float(_) => std::mem::size_of::<f64>(),
        Value::Bool(_) => std::mem::size_of::<bool>(),
        _ => unreachable!(),
    };

    // Skip quarantine cleanup, allocate directly
    let address = manager.next_address;
    manager.next_address += size.max(8);

    // Simplified safety check
    // ... Create memory block and pointer tags
}
🧠 Intelligent Path Selection
/// 🚀 v0.6.3 Smart Memory Allocation - Selects fast/safe path based on type
pub fn allocate_memory_smart(value: Value) -> Result<(usize, u64), String> {
    match &value {
        Value::Int(_) | Value::Float(_) | Value::Bool(_) | Value::Long(_) => {
            // Fast path for simple types
            allocate_simple_type_fast(value)
        },
        _ => {
            // Full security path for complex types
            let mut manager = MEMORY_MANAGER.write().unwrap();
            manager.allocate(value)
        }
    }
}

Performance Test Results

📊 Comparison with Python Performance
Test Type CodeNothing v0.6.3 Python 3.x Performance Comparison
IO-intensive (100k loops + output) 6.2s 8.8s 42% faster ✅
Memory-intensive (160k complex ops) 51.8s - New test
Simple computation (100k simple ops) 28.4s 0.049s Requires optimization ⚠️
🔍 Performance Analysis
  • Advantageous Areas: IO-intensive and complex memory operations
  • Improvement Space: Simple computation loops require JIT optimization
  • Architectural Value: Lays foundation for future smart allocation optimizations

Optimization Results

✅ Achievements
  1. Type-aware Allocation: Automatically identifies simple types and uses fast paths
  2. Reduced Overhead: Simple types skip complex isolation mechanisms and security checks
  3. Inline Optimization: Inlined size calculation reduces function call overhead
  4. Backward Compatibility: Maintains existing functionality and security
🎯 Technical Highlights
  • Zero-configuration: User code requires no modifications to benefit
  • Safety First: Full security checks maintained for complex types
  • Extensible: Provides architectural foundation for future optimizations

Benchmark Tests

Memory-intensive Test
// Testing massive simple type allocation
while (i < 50000) {
    value1 : int = i * 2;      // Fast path
    value2 : int = i + 100;    // Fast path
    float_val : float = 3.14;  // Fast path
    bool_val : bool = true;    // Fast path
    long_val : long = 1000000; // Fast path
    str_val : string = "test"; // Security path
    i = i + 1;
}

Result: Completed 160k complex operations in 51.8s

IO-intensive Test
    while (i < 30000) {
        // Creates temporary variables for output each loop
        value : int = i * 2;
        std::println("Number: " + value);
        i = i + 1;
    };

Result: 6.2s, 42% faster than Python

🔮 Future Optimization Directions

Based on v0.6.3 findings, next optimization priorities:

  1. v0.6.4 JIT Compilation: Just-In-Time compilation for hot loops
  2. v0.6.5 Expression Caching: Cache results of frequently used expressions
  3. v0.7.0 Bytecode VM: Compile AST into bytecode for execution

🐛 Known Limitations

  • Simple Loop Performance: Requires JIT optimization for pure computation loops
  • Interpreter Overhead: AST traversal overhead requires bytecode optimization
  • Type Checking: Runtime type checking still has optimization potential

[v0.6.3] - 2025-08-02

🚀 简单类型快速路径优化

核心改进

  • 智能内存分配: 实现基于类型的智能内存分配策略，简单类型使用快速路径
  • 性能优化: 为 int、float、bool、long 等简单类型提供优化的内存分配
  • 安全保障: 复杂类型保持完整的安全检查机制，确保内存安全

技术实现

🎯 简单类型快速分配
/// 🚀 v0.6.3 简单类型快速分配函数 - 跳过复杂安全检查
fn allocate_simple_type_fast(value: Value) -> Result<(usize, u64), String> {
    let mut manager = MEMORY_MANAGER.write().unwrap();

    // 内联大小计算，避免函数调用开销
    let size = match &value {
        Value::Int(_) => std::mem::size_of::<i32>(),
        Value::Long(_) => std::mem::size_of::<i64>(),
        Value::Float(_) => std::mem::size_of::<f64>(),
        Value::Bool(_) => std::mem::size_of::<bool>(),
        _ => unreachable!(),
    };

    // 跳过隔离区清理，直接分配
    let address = manager.next_address;
    manager.next_address += size.max(8);

    // 简化的安全检查
    // ... 创建内存块和指针标记
}
🧠 智能路径选择
/// 🚀 v0.6.3 智能内存分配 - 根据类型选择快速或安全路径
pub fn allocate_memory_smart(value: Value) -> Result<(usize, u64), String> {
    match &value {
        Value::Int(_) | Value::Float(_) | Value::Bool(_) | Value::Long(_) => {
            // 简单类型使用快速路径
            allocate_simple_type_fast(value)
        },
        _ => {
            // 复杂类型使用完整的安全路径
            let mut manager = MEMORY_MANAGER.write().unwrap();
            manager.allocate(value)
        }
    }
}

性能测试结果

📊 与Python性能对比
测试类型 CodeNothing v0.6.3 Python 3.x 性能对比
IO密集型 (10万次循环+输出) 6.2秒 8.8秒 快42% ✅
内存密集型 (16万次复杂操作) 51.8秒 - 新测试
简单计算 (10万次简单操作) 28.4秒 0.049秒 需优化 ⚠️
🔍 性能分析
  • 优势领域: IO密集型和复杂内存操作场景
  • 改进空间: 简单计算循环需要JIT编译优化
  • 架构价值: 为未来优化奠定了智能分配基础

优化效果

✅ 成功实现
  1. 类型感知分配: 自动识别简单类型并使用快速路径
  2. 开销减少: 简单类型跳过复杂的隔离机制和安全检查
  3. 内联优化: 大小计算内联，减少函数调用开销
  4. 向后兼容: 不影响现有代码功能和安全性
🎯 技术亮点
  • 零配置: 用户代码无需修改，自动享受优化
  • 安全第一: 复杂类型保持完整安全检查
  • 可扩展: 为未来更多优化提供架构基础

基准测试

内存密集型测试
// 测试大量简单类型分配
while (i < 50000) {
    value1 : int = i * 2;      // 快速路径
    value2 : int = i + 100;    // 快速路径
    float_val : float = 3.14;  // 快速路径
    bool_val : bool = true;    // 快速路径
    long_val : long = 1000000; // 快速路径
    str_val : string = "test"; // 安全路径
    i = i + 1;
}

结果: 51.8秒完成16万次复杂操作

IO密集型测试
    while (i < 30000) {
        // 每次循环都会创建临时变量进行输出
        value : int = i * 2;
        std::println("数字: " + value);
        i = i + 1;
    };

结果: 6.2秒，比Python快42%

🔮 未来优化方向

基于v0.6.3的发现，下一步优化重点：

  1. v0.6.4 JIT编译: 对热点循环进行即时编译
  2. v0.6.5 表达式缓存: 缓存常用表达式计算结果
  3. v0.7.0 字节码虚拟机: 编译AST为字节码执行

🐛 已知限制

  • 简单循环性能: 在纯计算循环中仍需JIT优化
  • 解释器开销: AST遍历开销需要字节码优化解决
  • 类型检查: 运行时类型检查仍有优化空间

Full Changelog: CodeNothingCommunity/CodeNothing@v0.6.2...v0.6.3

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