quant-ai / cpp_engine /include /lockfree_queue.hpp
Ypeng12's picture
feat(ai): add cpp low latency engine and advanced ml alpha models
ae5ecc5
Raw History Blame Contribute Delete
1.82 kB
#ifndef LOCKFREE_QUEUE_HPP
#define LOCKFREE_QUEUE_HPP
#include <atomic>
#include <cstddef>
#include <vector>
#include <optional>
#include <stdexcept>
namespace quant {
/**
* Lock-Free Single-Producer Single-Consumer (SPSC) RingBuffer Queue.
* Optimized for microsecond event dispatching in High-Frequency Quant Trading.
*/
template <typename T, size_t Capacity = 1024>
class LockFreeSPSCQueue {
static_assert((Capacity & (Capacity - 1)) == 0, "Capacity must be a power of two");
public:
LockFreeSPSCQueue() : head_(0), tail_(0) {
buffer_.resize(Capacity);
}
bool push(const T& item) {
const size_t current_tail = tail_.load(std::memory_order_relaxed);
const size_t current_head = head_.load(std::memory_order_acquire);
if ((current_tail - current_head) >= Capacity) {
return false; // Queue Full
}
buffer_[current_tail & (Capacity - 1)] = item;
tail_.store(current_tail + 1, std::memory_order_release);
return true;
}
std::optional<T> pop() {
const size_t current_head = head_.load(std::memory_order_relaxed);
const size_t current_tail = tail_.load(std::memory_order_acquire);
if (current_head == current_tail) {
return std::nullopt; // Queue Empty
}
T item = buffer_[current_head & (Capacity - 1)];
head_.store(current_head + 1, std::memory_order_release);
return item;
}
size_t size() const {
return tail_.load(std::memory_order_relaxed) - head_.load(std::memory_order_relaxed);
}
bool empty() const {
return size() == 0;
}
private:
std::vector<T> buffer_;
alignas(64) std::atomic<size_t> head_;
alignas(64) std::atomic<size_t> tail_;
};
} // namespace quant
#endif // LOCKFREE_QUEUE_HPP