Large Scale Data Clustering Using Memristive k-Median Computation

Abstract

Clustering is a crucial tool for analyzing data in virtually every scientific and engineering discipline. The U.S. National Academy of Sciences (NAS) has recently announced "the seven giants of statistical data analysis" in which data clustering plays a central role [1]. This research also emphasizes that more scalable solutions are required to enable time and space clustering for the future large-scale data analyses. Therefore, hardware and software innovations are necessary to make the future large scale data analysis practical.This project proposes a novel mechanism for computing bit serial medians within resistive RAM (RRAM) arrays with no need to read out the operands from memory cells.