A fast updatable implementation of index generation functions using multiple IGUs

Tsutomu Sasao

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This paper presents a method to realize index generation functions using multiple Index Generation Units (IGUs). The architecture implements index generation functions more efficiently than a single IGU when the number of registered vectors is very large. This paper proves that independent linear transformations are necessary in IGUs for efficient realization. Experimental results confirm this statement. Finally, it shows a fast update method to IGUs.

Original languageEnglish
Pages (from-to)1574-1582
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE100D
Issue number8
DOIs
Publication statusPublished - Aug 2017

Keywords

  • CAM
  • Content-addressable memory
  • Linear decomposition
  • Linear transformation
  • Random function
  • Statistical analysis
  • Update method

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