Berti: an Accurate Local-Delta Data Prefetcher

Navarro-Torres, Agustin (Universidad de Zaragoza) ; Panda, Biswabandan ; Alastruey-Benede, Jesus (Universidad de Zaragoza) ; Ibañez, Pablo (Universidad de Zaragoza) ; Viñals-Yufera, Victor (Universidad de Zaragoza) ; Ros, Alberto

Resumen: Data prefetching is a technique that plays a crucial role in modern high-performance processors by hiding long latency memory accesses. Several state-of-the-art hardware prefetchers exploit the concept of deltas, defined as the difference between the cache line addresses of two demand accesses. Existing delta prefetchers, such as best offset prefetching (BOP) and multi-lookahead prefetching (MLOP), train and predict future accesses based on global deltas. We observed that the use of global deltas results in missed opportunities to anticipate memory accesses. In this paper, we propose Berti, a first-level data cache prefetcher that selects the best local deltas, i.e., those that consider only demand accesses issued by the same instruction. Thanks to a high-confidence mechanism that precisely detects the timely local deltas with high coverage, Berti generates accurate prefetch requests. Then, it orchestrates the prefetch requests to the memory hierarchy, using the selected deltas. Our empirical results using ChampSim and SPEC CPU2017 and GAP workloads show that, with a storage overhead of just 2.55 KB, Berti improves performance by 8.5% compared to a baseline IP-stride and 3.5% compared to IPCP, a state-of-the-art prefetcher. Our evaluation also shows that Berti reduces dynamic energy at the memory hierarchy by 33.6% compared to IPCP, thanks to its high prefetch accuracy.

Idioma: Inglés

DOI: 10.1109/MICRO56248.2022.00072

Año: 2022

Publicado en: Proceedings of the Annual International Symposium on Microarchitecture, MICRO 55 (2022), 975-991
ISSN: 1072-4451

Financiación: info:eu-repo/grantAgreement/ES/AEI-FEDER/PID2019-105660RB-C21
Financiación: info:eu-repo/grantAgreement/ES/AEI-FEDER/RTI2018-098156-B-C53
Financiación: info:eu-repo/grantAgreement/ES/DGA-ESF/T58-20R
Financiación: info:eu-repo/grantAgreement/EC/H2020/819134/EU/Extending Coherence for Hardware-Driven Optimizations in Multicore Architectures/ECHO

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Arquit.Tecnología Comput. (Dpto. Informát.Ingenie.Sistms.)