ParRP: Enabling Space Isolation in Caches with Shared Data

This work presents an approach to isolate cache space while supporting shared data. Enabling shared data caching is challenging because it causes interference making it unsuitable for real-time multicores. Unlike prior works, we aim to introduce isolation, but our approach enables caching of shared data, and promotes isolated cache analysis for individual cores. The crux behind our approach is that shared data isolation can be achieved by partitioning the replacement information instead of the cache's data storage. Consequently, this work introduces ParRP, a novel hardware cache partitioning scheme for realtime cache-coherent multicores. Our evaluation using the gem5 simulator shows that, by providing isolation for shared data, the worst-case execution time of multi-threaded tasks can be lower by 2.4× at the cost of a 16.5% decrease in average-case performance.

Authors

Institutions

Publication Details

Published
2025-05-06
DOI
https://doi.org/10.1109/rtas65571.2025.00020
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ParRP: Enabling Space Isolation in Caches with Shared Data

Rodolfo Pellizzoni, Hiren Patel, Xinzhe Wang
Context-Aware Activity Recognition Systems
article

ParRP: Enabling Space Isolation in Caches with Shared Data

Rodolfo Pellizzoni, Hiren Patel, Xinzhe Wang
article en

Abstract

This work presents an approach to isolate cache space while supporting shared data. Enabling shared data caching is challenging because it causes interference making it unsuitable for real-time multicores. Unlike prior works, we aim to introduce isolation, but our approach enables caching of shared data, and promotes isolated cache analysis for individual cores. The crux behind our approach is that shared data isolation can be achieved by partitioning the replacement information instead of the cache's data storage. Consequently, this work introduces ParRP, a novel hardware cache partitioning scheme for realtime cache-coherent multicores. Our evaluation using the gem5 simulator shows that, by providing isolation for shared data, the worst-case execution time of multi-threaded tasks can be lower by 2.4× at the cost of a 16.5% decrease in average-case performance.

University of Waterloo (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 89%
Context-Aware Activity Recognition Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.