Home  >  Article  >  Backend Development  >  Performance optimization of C++ in high-frequency trading

Performance optimization of C++ in high-frequency trading

WBOY
WBOYOriginal
2024-06-01 21:23:021123browse

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.

Performance optimization of C++ in high-frequency trading

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.

The above is the detailed content of Performance optimization of C++ in high-frequency trading. For more information, please follow other related articles on the PHP Chinese website!

Statement:
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn