Access Adaptive and Thread-Aware Cache Partitioning in Multicore Systems

Abstract

Cache partitioning is a successful technique for saving energy for a shared cache and all the existing studies focus on multi-program workloads running in multicore systems. In this paper, we are motivated by the fact that a multi-thread application generally executes faster than its single-thread counterpart and its cache accessing behavior is quite different. Based on this observation, we study applications running in multi-thread mode and classify data of the multi-thread applications into shared and private categories, which helps reduce the interferences among shared and private data and contributes to constructing a more efficient cache partitioning scheme. We also propose a hardware structure to support these operations. Then, an access adaptive and thread-aware cache partitioning (ATCP) scheme is proposed, which assigns separate cache portions to shared and private data to avoid the evictions caused by the conflicts from the data of different categories in the shared cache. The proposed ATCP achieves a lower energy consumption, meanwhile improving the performance of applications compared with the least recently used (LRU) managed, core-based evenly partitioning (EVEN) and utility-based cache partitioning (UCP) schemes. The experimental results show that ATCP can achieve 29.6% and 19.9% average energy savings compared with LRU and UCP schemes in a quad-core system. Moreover, the average speedup of multi-thread ATCP with respect to single-thread LRU is at 1.89.