A. Delegato: Locality-Aware Atomic Memory Operations on Chiplets

The irruption of chiplet-based architectures has been a game changer, enabling higher transistor integration and core counts in a single socket.However, chiplets impose higher and non-uniform memory access (NUMA) latencies than monolithic integration.This harms the efficiency of atomic memory operations (AMOs), which are fundamental to implementing fine-grained synchronization and concurrent data structures on large systems.AMOs are executed either near the core (near) or at a remote location within the cache hierarchy (far).On near AMOs, the core's private cache fetches the target cache line in exclusiveness to modify it locally.Near AMOs cause significant data movement between private caches, especially harming parallel applications' performance on chiplet-based architectures.Alternatively, far AMOs can alleviate the communication overhead by reducing data movement between processing elements.However, current multicore architectures only support one type of far AMO, which sends all updates to a single serialization point (centralized AMOs).This work introduces two new types of far AMOs, delegated and migrating, that execute AMOs remotely without centralizing updates in a single point of the cache hierarchy.Combining centralized, delegated, and migrating AMOs allows the directory to select the best location to execute AMOs.Moreover, we propose Delegato, a tracing optimization to effectively transport usage information from private caches to the directory to predict the best atomic type to issue accurately.Additionally, we design a simple predictor on