Building Low-Latency Trading Systems

In high-frequency trading, microseconds matter. Building systems that consistently deliver sub-millisecond latency requires careful attention to every layer of the stack.

The Latency Budget

Understanding where time goes is crucial:

Component	Typical Latency
Network (same DC)	10-50 μs
Kernel bypass (DPDK)	1-5 μs
Application logic	5-20 μs
Market data parsing	1-3 μs
Order generation	2-5 μs

Every microsecond saved compounds across millions of messages.

Hardware Considerations

The foundation starts with hardware:

• CPU: Modern processors with high clock speeds and large L3 caches
• NUMA awareness: Keep data and threads on same socket
• NIC: Low-latency network cards with kernel bypass
• Memory: Fast RAM with low CAS latency

Software Architecture

Kernel Bypass

Traditional networking goes through the kernel. Kernel bypass (DPDK, RDMA) eliminates this overhead:

// Traditional socket
recv(socket_fd, buffer, size, 0);  // ~50μs

// DPDK
rte_eth_rx_burst(port_id, queue_id, pkts, MAX_BURST);  // ~2μs

Lock-Free Data Structures

Locks are latency killers. Lock-free queues enable thread communication without blocking:

// Lock-free ring buffer
template<typename T, size_t SIZE>
class LockFreeQueue {
    std::atomic<size_t> head{0};
    std::atomic<size_t> tail{0};
    T buffer[SIZE];

    bool push(const T& item) {
        size_t current_tail = tail.load(std::memory_order_relaxed);
        size_t next_tail = (current_tail + 1) % SIZE;

        if (next_tail == head.load(std::memory_order_acquire))
            return false;

        buffer[current_tail] = item;
        tail.store(next_tail, std::memory_order_release);
        return true;
    }
};

Memory Management

Dynamic allocation is unpredictable. Pre-allocate everything:

• Object pools for order structures
• Ring buffers for message passing
• Huge pages to reduce TLB misses

Optimization Techniques

CPU Pinning

Bind critical threads to specific cores:

taskset -c 2,3 ./trading_engine

Compiler Optimizations

// Branch prediction hints
if (__builtin_expect(is_market_order, 1)) {
    // Fast path
}

// Prefetching
__builtin_prefetch(&market_data[i+1]);

// Likely/unlikely
[[likely]]
[[unlikely]]

Cache Optimization

• Align data structures to cache lines (64 bytes)
• False sharing elimination
• Hot/cold path separation

Monitoring and Measurement

You can't optimize what you don't measure:

• TSC (Time Stamp Counter): Cycle-accurate timing
• Percentile analysis: P50, P99, P99.9
• Histograms: Latency distribution visualization

uint64_t start = __rdtsc();
process_order(order);
uint64_t end = __rdtsc();
uint64_t cycles = end - start;

Trade-offs

Low latency comes with costs:

• Increased complexity
• Higher resource usage (dedicated cores, memory)
• More difficult debugging
• Reduced flexibility

The key is knowing when these trade-offs are justified.