Feedback-Driven Runtime Adaptation for Synchronization Primitives

Abstract

Modern multithreaded applications operate under highly dynamic execution conditions, where contention patterns on shared data structures vary significantly over time due to phase changes, workload skew, and platform-specific scheduling effects. Conventional synchronization primitives—such as pure spin locks, queue-based locks, or blocking mutexes—are static by design and therefore optimized for only a narrow operating regime. As a result, developers are forced to choose a single synchronization strategy that may perform well in one phase but poorly in another. 

This paper presents Feedback-Driven Runtime Adaptation for Synchronization Primitives, a practical framework that treats synchronization as a closed-loop control problem. Rather than proposing a new lock algorithm, we continuously observe lightweight contention telemetry, estimate runtime pressure, and adapt synchronization behavior using simple, explainable policies augmented with explicit stability constraints. We instantiate the framework for a mutex-like primitive in portable user-space C++ and evaluate it on a modern ARM-based Apple M1 system under non-stationary workloads. Experimental results demonstrate that feedback-driven adaptation induces bounded and meaningful behavioral changes under contention, trading peak throughput for improved predictability and robustness while avoiding oscillatory behavior. The results confirm that controlled runtime adaptation provides a viable alternative to static synchronization strategies in modern systems.