Dynamic tag-check omission: A low power instruction cache architecture exploiting execution footprints

Koji Inoue, Vasily Moshnyaga, Kazuaki Murakami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an architecture for low-power directmapped instruction caches, called “history-based tag-comparison (HBTC) cache”. The HBTC cache attempts to detect and omit unnecessary tag checks at run time. Execution footprints are recorded in an extended BTB (Branch Target Buffer), and are used to know the cache residence of target instructions before starting cache access. In our simulation, it is observed that our approach can reduce the total count of tag checks by 90 %, resulting in 15 % of cache-energy reduction, with less than 0.5 % performance degradation.

Original languageEnglish
Title of host publicationPower-Aware Computer Systems - 2nd International Workshop, PACS 2002, Revised Papers
EditorsBabak Falsafi, T.N. Vijaykumar
PublisherSpringer Verlag
Pages18-32
Number of pages15
ISBN (Print)3540010289, 9783540010289
DOIs
Publication statusPublished - Jan 1 2003
Event2nd International Workshop on Power-Aware Computer Systems, PACS 2002 - Cambridge, United States
Duration: Feb 2 2002Feb 2 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2325
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Workshop on Power-Aware Computer Systems, PACS 2002
CountryUnited States
CityCambridge
Period2/2/022/2/02

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Inoue, K., Moshnyaga, V., & Murakami, K. (2003). Dynamic tag-check omission: A low power instruction cache architecture exploiting execution footprints. In B. Falsafi, & T. N. Vijaykumar (Eds.), Power-Aware Computer Systems - 2nd International Workshop, PACS 2002, Revised Papers (pp. 18-32). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2325). Springer Verlag. https://doi.org/10.1007/3-540-36612-1_2