POSTER: An Architecture and Programming Model for Accelerating Parallel Commutative Computations via Privatization

Abstract

Synchronization and data movement are the key impediments to an efficient parallel execution. To ensure that data shared by multiple threads remain consistent, the programmer must use synchronization (e.g., mutex locks) to serialize threads' accesses to data. This limits parallelism because it forces threads to sequentially access shared resources. Additionally, systems use cache coherence to ensure that processors always operate on the most up-to-date version of a value even in the presence of private caches. Coherence protocol implementations cause processors to serialize their accesses to shared data, further limiting parallelism and performance.