Low Latency

In high-frequency trading (HFT), microseconds determine profitability. When an arbitrage opportunity appears—say, a 0.01% price discrepancy between two exchanges—it vanishes within 100-500 microseconds as competing algorithms exploit it. The firm that detects and acts fastest captures the profit; everyone else loses. At this timescale, traditional software engineering practices (dynamic allocation, garbage collection, high-level abstractions) become liabilities. Systems must operate at the edge of hardware capability: cache-line optimization, lock-free algorithms, kernel bypass networking. ...

In 2019, a quantitative trading firm discovered their portfolio risk calculation was bottlenecked not by algorithmic complexity, but by memory access patterns. By restructuring their data layout and applying SIMD vectorization, they reduced computation time from 47 seconds to 890 milliseconds—a 53× speedup—without changing a single line of business logic. The difference between naive and optimized vector operations isn’t just academic; it’s the difference between real-time decision making and stale analysis in production systems. ...