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Governing with Insights: Towards Profile-Driven Cache Management of Black-Box Applications

Authors Golsana Ghaemi, Dharmesh Tarapore, Renato Mancuso

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Author Details

Golsana Ghaemi
  • Boston University, MA, USA
Dharmesh Tarapore
  • Boston University, MA, USA
Renato Mancuso
  • Boston University, MA, USA

Funding

  • Mancuso, Renato: The material presented in this paper is based upon work supported by the National Science Foundation (NSF) under grant number CCF-2008799. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the NSF.

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Golsana Ghaemi, Dharmesh Tarapore, and Renato Mancuso. Governing with Insights: Towards Profile-Driven Cache Management of Black-Box Applications. In 33rd Euromicro Conference on Real-Time Systems (ECRTS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 196, pp. 4:1-4:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.ECRTS.2021.4

Abstract

There exists a divide between the ever-increasing demand for high-performance embedded systems and the availability of practical methodologies to understand the interplay of complex data-intensive applications with hardware memory resources. On the one hand, traditional static analysis approaches are seldomly applicable to latest-generation multi-core platforms due to a lack of accurate micro-architectural models. On the other hand, measurement-based methods only provide coarse-grained information about the end-to-end execution of a given real-time application.
In this paper, we describe a novel methodology, namely Black-Box Profiling (BBProf), to gather fine-grained insights on the usage of cache resources in applications of realistic complexity. The goal of our technique is to extract the relative importance of individual memory pages towards the overall temporal behavior of a target application. Importantly, BBProf does not require the semantics of the target application to be known - i.e., applications are treated as black-boxes - and it does not rely on any platform-specific hardware support. We provide an open-source full-system implementation and showcase how BBProf can be used to perform profile-driven cache management.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Real-time system architecture
Keywords
  • Cache Profiling
  • WSS Estimation
  • Cache Interference
  • Real-time
  • Multicore
  • Contention-induced Instruction Stall
  • C2IS
  • Coloring
  • Cache Management
  • Cacheability

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