Niloofar Charmchi successfully defended her PhD on Friday, July 10, 2020 at 10am.
Jury members
Rapporteurs :
- Karine HEYDEMANN Maîtresse de conférence, Sorbonne Université
- David DEFOUR Maître de conférence, Université de Perpignan Via Domitia
Examinateurs :
- Florent DE DINECHIN Professeur des universités, INSA Lyon
- Steven DERRIEN Professeur des universités, Université Rennes 1
Directeur de thèse : André Seznec Directeur de recherches, Inria
Co-dir. de thèse : Caroline Collange Chargée de recherche, Inria
Title : Compressed Cache Layout Aware Prefetching
Abstract: The speed gap between CPU and memory is impairing performance. Cache compression and hardware prefetching are two techniques that could confront this bottleneck by decreasing last level cache misses. However, compression and prefetching have positive interactions, as prefetching benefits from higher cache capacity and compression increases the effective cache size. This study proposes Compressed cache Layout Aware Prefetching (CLAP) to leverage the recently proposed sector-based compressed cache layouts, such as SCC or YACC, to create a synergy between compressed caches and prefetching. The idea of this approach is to prefetch contiguous blocks that can be compressed and co-allocated together with the requested block on a miss access. Prefetched blocks that share storage with existing blocks do not need to evict a valid existing entry; therefore, CLAP avoids cache pollution. In order to decide the co-allocatable blocks to prefetch, we propose a compression predictor. Based on our experimental evaluations, CLAP reduces the number of cache misses by 9% and improves performance by 3% on average, comparing to a compressed cache. Fur thermore, in order to get more improvements, we unify CLAP and other prefetchers and introduce two adaptive CLAPs which select the best prefetcher based on the application.
