As multicore processors become increasingly prevalent, system complexity is skyrocketing. The advent of the asymmetric multicore compounds this - it is no longer practical for an average programmer to balance the system constraints associated with today's multicores and worry about new problems like asymmetric partitioning and thread interference. Adaptive, or self-aware, computing has been proposed as one method to help application and system programmers confront this complexity. These systems take some of the burden off of programmers by monitoring themselves and optimizing or adapting to meet their goals. This paper introduces a self-aware synchronization library for multicores and asymmetric multicores called Smartlocks. Smartlocks is a spin-lock library that adapts its internal implementation during execution using heuristics and machine learning to optimize toward a user-defined goal, which may relate to performance or problem-specific criteria. Smartlocks builds upon adaptation techniques from prior work like reactive locks [1], but introduces a novel form of adaptation that we term lock acquisition scheduling designed specifically to address asymmetries in multicores. Lock acquisition scheduling is optimizing which waiter will get the lock next for the best long-term effect when multiple threads (or processes) are spinning for a lock. This work demonstrates that lock scheduling is important for addressing asymmetries in multicores. We study scenarios where core speeds vary both dynamically and intrinsically under thermal throttling and manufacturing variability, respectively, and we show that Smartlocks significantly outperforms conventional spin-locks and reactive locks. Based on our findings, we provide guidelines for application scenarios where Smartlocks works best versus less optimally.