C++ memory pool and early allocation to improve memory management performance

Two techniques to improve memory management performance in C++: Memory pool: Pre-allocate large blocks of memory and divide them into small blocks, providing fast allocation and release, reducing the overhead of interacting with the operating system. Advance allocation: Pre-allocate a large amount of memory when the program starts, avoiding the delay in requesting memory from the operating system and achieving rapid allocation.

C++ Memory Pool and Early Allocation: Improving Memory Management Performance

Introduction

Memory management is an important aspect of C++ development. Efficient memory management can significantly improve application performance and stability. This article will explore two memory management techniques in C++: memory pools and early allocation, and show how to use them to improve memory management performance.

Memory pool

Memory pool is a memory management technology that pre-allocates a large memory block and then divides the block into small blocks of even size. When memory is needed, applications can allocate small chunks from the pool without requesting it from the operating system.

#include <iostream>
#include <vector>

class MemoryPool {
private:
    std::vector<void*> freeBlocks;
    std::vector<void*> allocatedBlocks;
    size_t blockSize;
    size_t poolSize;

public:
    MemoryPool(size_t blockSize, size_t poolSize)
        : blockSize(blockSize), poolSize(poolSize) {
        for (size_t i = 0; i < poolSize; ++i) {
            freeBlocks.push_back(malloc(blockSize));
        }
    }

    ~MemoryPool() {
        for (auto block : allocatedBlocks) {
            free(block);
        }
    }

    void* allocate() {
        if (freeBlocks.empty()) {
            return nullptr;
        }
        void* block = freeBlocks.back();
        freeBlocks.pop_back();
        allocatedBlocks.push_back(block);
        return block;
    }

    void deallocate(void* block) {
        freeBlocks.push_back(block);
        allocatedBlocks.erase(std::remove(allocatedBlocks.begin(), allocatedBlocks.end(), block));
    }
};

int main() {
    MemoryPool pool(1024, 100);

    std::vector<void*> objects;
    for (size_t i = 0; i < 100; ++i) {
        objects.push_back(pool.allocate());
    }

    // 使用对象

    for (auto object : objects) {
        pool.deallocate(object);
    }

    return 0;
}

Early allocation

Early allocation is a technique that allocates a large amount of memory in advance when the program starts. This memory is not used immediately, but is quickly allocated when needed, avoiding the delay of requesting memory from the operating system.

#include <iostream>
#include <vector>

std::vector<int> preallocatedMemory(1000000);

int main() {
    // 记录内存分配时间
    auto start = std::chrono::high_resolution_clock::now();

    std::vector<int> objects;
    for (size_t i = 0; i < 1000000; ++i) {
        objects.push_back(preallocatedMemory[i]);
    }

    // 计算内存分配时间
    auto end = std::chrono::high_resolution_clock::now();
    auto duration = std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count();

    std::cout << "Memory allocation time: " << duration << " ms\n";

    return 0;
}

Practical case

Memory pool and early allocation technology are particularly useful in the following scenarios:

• Game development: the game requires fast and frequent allocation and release memory to create and destroy game objects.
• Web Server: A web server needs to handle a large number of connections, each of which requires its own memory allocation.
• High Performance Computing: High performance computing applications process large amounts of data and require efficient memory management to maximize performance.

Conclusion

The performance of memory management in C++ applications can be significantly improved by using memory pools and early allocation techniques. These techniques reduce the overhead of requesting memory from the operating system, enabling faster allocation and deallocation operations and improving overall application performance.

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