A Real-Time Learning Processor Based on K-means Algorithm with Automatic Seeds Generation

Abstract

A full-custom learning processor architecture has been developed based on the K-means algorithm aiming at realtime clustering applications. In order to accelerate the convergence and improve the quality of solutions, an automatic initial seeds generation function has been implemented in the architecture. The concept has been verified by the measurement of the proof-of-concept chip designed and fabricated in a 0.18-mum 5-metal CMOS technology. A full custom chip was also designed using the same technology and sent to fabrication and its operation was confirmed by simulation.