A parallel architecture for high-speed data compression

Published

Journal Article

Data compression is becoming an essential component of high-speed data datmunications and storage. Lossless data compression is when the decompressed data must be identical to the original. Textual substitution methods are among the most powerful approaches to lossless data compression, where repeated substrings are replaced by pointers into a dynamically changing dictionary of strings. We present a massively parallel architecture for textual substitution that is based on a systolic pipe of 3839 identical processing elements that forms what is essentially an associative memory for strings that can "learn" new strings on the basis of the text processed thus far. Key to the design of this architecture is the formulation of an inherently "top-down" serial learning strategy as a "bottom-up" parallel strategy. A custom VLSI chip for this architecture that operates at 320 million bits per second has been fabricated. © 1991.

Full Text

Duke Authors

Cited Authors

  • Storer, JA; Reif, JH

Published Date

  • January 1, 1991

Published In

Volume / Issue

  • 13 / 2

Start / End Page

  • 222 - 227

International Standard Serial Number (ISSN)

  • 0743-7315

Digital Object Identifier (DOI)

  • 10.1016/0743-7315(91)90091-M

Citation Source

  • Scopus