A Fast Updatable Implementation of Index Generation Functions Using Multiple IGUs

作者：Sasao Tsutomu^*

来源：IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2017, E100D(8): 1574-1582.

DOI：10.1587/transinf.2016LOP0001

• random function
• CAM
• content-addressable memory
• linear decomposition
• linear transformation
• statistical analysis
• update method

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.

• 出版日期2017-8