A Fast Updatable Implementation of Index Generation Functions Using Multiple IGUs

Tsutomu SASAO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.8   pp.1574-1582
Publication Date: 2017/08/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016LOP0001
Type of Manuscript: Special Section PAPER (Special Section on Multiple-Valued Logic and VLSI Computing)
Category: Logic Design
Keyword: 
random function,  CAM,  content-addressable memory,  linear decomposition,  linear transformation,  statistical analysis,  update method,  

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Summary: 
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.