On the value of multiple read/write streams for data compression

  • Authors:
  • Travis Gagie

  • Affiliations:
  • Department of Computer Science and Engineering, Aalto University, Finland

  • Venue:
  • Information Theory, Combinatorics, and Search Theory
  • Year:
  • 2013

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Abstract

We study whether, when restricted to using polylogarithmic memory and polylogarithmic passes, we can achieve qualitatively better data compression with multiple read/write streams than we can with only one. We first show how we can achieve universal compression using only one pass over one stream. We then show that one stream is not sufficient for us to achieve good grammar-based compression. Finally, we show that two streams are necessary and sufficient for us to achieve entropy-only bounds.