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Conditional branches pose a challenge for code optimisation, particularly inlow latency settings. For better performance, processors leverage dedicatedhardware to predict the outcome of a branch and execute the followinginstructions speculatively, a powerful optimisation. Modern branch predictorsemploy sophisticated algorithms and heuristics that utilise historical data andpatterns to make predictions, and often, are extremely effective at doing so.Consequently, programmers may inadvertently underestimate the cost ofmisprediction when benchmarking code with synthetic data that is either tooshort or too predictable. While eliminating branches may not always befeasible, C++20 introduced the [[likely]] and [[unlikely]] attributes thatenable the compiler to perform spot optimisations on assembly code associatedwith likely execution paths. Can we do better than this?  This work presents the development of a novel language construct, referred toas a semi-static condition, which enables programmers to dynamically modify thedirection of a branch at run-time by modifying the assembly code within theunderlying executable. Subsequently, we explore scenarios where the use ofsemi-static conditions outperforms traditional conditional branching,highlighting their potential applications in real-time machine learning andhigh-frequency trading. Throughout the development process, key considerationsof performance, portability, syntax, and security were taken into account.

Semi-static Conditions in Low-latency C++ for High Frequency Trading: Better than Branch Prediction Hints