PMOP: Efficient Per-Page Most-Offset Prefetcher
Kanghee Kim, Wooseok Lee, Sang-Bang Choi · IEICE Transactions on Information and Systems · 2019
Hardware prefetching involves a sophisticated balance between accuracy, coverage, and timeliness while minimizing hardware cost.Recent prefetchers have achieved these goals, but they still require complex hardware and a significant amount of storage.In this paper, we propose an efficient Per-page Most-Offset Prefetcher (PMOP) that minimizes hardware cost and simultaneously improves accuracy while maintaining coverage and timeliness.We achieve these objectives using an enhanced offset prefetcher that performs well with a reasonable hardware cost.Our approach first addresses coverage and timeliness by allowing multiple Most-Offset predictions.To minimize offset interference between pages, the PMOP leverages a fine-grain per-page offset filter.This filter records the access history with page-IDs, which enables efficient mapping and tracking of multiple offset streams from diverse pages.Analysis results show that PMOP outperforms the state-of-the-art Signature Path Prefetcher while reducing storage overhead by a factor of 3.4.