Performance optimization of C++ in high-frequency trading

C Optimize performance in high-frequency trading through the following techniques: reducing memory allocation and deallocation; optimizing data structures (such as hash tables and B-trees); using caching; leveraging multi-threaded programming.

C Performance optimization in high-frequency trading

Introduction
In the field of high-frequency trading, performance is crucial , any slight delay may result in trading losses. C is known for its efficient and low-latency properties, making it ideal for high-frequency trading tasks. This article will explore C's various techniques for improving performance in high-frequency trading.

Optimization Notes

• Reduce allocation and release of memory: Use memory pool or RAII (resource acquisition is initialization) technology to avoid Memory is allocated and freed in every transaction.
• Optimize data structure: Choose a data structure suitable for the task, such as hash table or B-tree, to achieve fast search and insertion.
• Use cache: Store frequently accessed data in cache to reduce the latency of retrieval from main memory.
• Multi-threaded programming: Use multiple threads to execute tasks in parallel to improve overall throughput.

Practical case

Optimize data structure:

// 使用哈希表快速查找订单
std::unordered_map<int, Order> orders;

// 使用 B 树处理限价订单
std::multimap<double, Order> limit_orders;

Use cache:

// 缓存最近成交的价格
std::map<std::string, double> price_cache;

// 从缓存获取价格，避免从主存储器读取
double get_price(std::string symbol) {
    auto it = price_cache.find(symbol);
    if (it != price_cache.end()) return it->second;
    // 如果未在缓存中，从主存储器加载价格...
}

Multi-threaded programming:

// 并发处理订单
std::vector<std::thread> threads;
for (auto& order : orders) {
    threads.push_back(std::thread([&order] {
        // 处理订单...
    }));
}
for (auto& thread : threads) {
    thread.join();
}

By applying these optimization techniques, C developers can significantly improve the performance of high-frequency trading applications to compete in the highly competitive financial markets have an advantage.

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