Using data compression to increase energy savings in multi-bank memories

M. Kandemir, O. Ozturk, M. J. Irwin, I. Kolcu

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

New DRAM technologies such as SDRAMs, RDRAMs, EDRAMs, CDRAMs and others are vying to be the next standard in DRAMs and improve upon bandwidth limit of conventional DRAMs. With proliferation of poweraware systems, banked DRAM architecture has emerged as a promising candidate for reducing power. Prior work on optimizing applications in a banked memory environment has exclusively focused on uncompressed data. While this may be preferable from a performance viewpoint, it is not necessarily the best strategy as far as memory space utilization is considered. This is because compressing data in memory may reduce the number of memory banks it occupies and this, in turn, may enable a better use of low-power operating modes. In this paper, we explore the possibility of compressing infrequently used data for increasing effectiveness of low-power operating modes in banked DRAMs. Our experiments with five highly parallel array-based embedded applications indicate significant savings in memory energy over a technique that exploits lowpower modes but does not use data compression/decompression.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMarco Danelutto, Marco Vanneschi, Domenico Laforenza
PublisherSpringer Verlag
Pages310-317
Number of pages8
ISBN (Print)3540229248
DOIs
StatePublished - Jan 1 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3149
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kandemir, M., Ozturk, O., Irwin, M. J., & Kolcu, I. (2004). Using data compression to increase energy savings in multi-bank memories. In M. Danelutto, M. Vanneschi, & D. Laforenza (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 310-317). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3149). Springer Verlag. https://doi.org/10.1007/978-3-540-27866-5_40