Hirotsugu Shikano, Kiyoto Ito, Kazuhide Fujita, T. Shibata
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引用次数: 5
摘要
针对实时聚类应用,基于K-means算法开发了一种全定制学习处理器架构。为了加快收敛速度和提高解的质量,在该体系结构中实现了初始种子自动生成功能。该概念已通过采用0.18 μ m 5金属CMOS技术设计和制造的概念验证芯片的测量得到验证。采用相同的技术设计了一个完全定制的芯片,并将其送入制造,并通过仿真验证了其运行。
A Real-Time Learning Processor Based on K-means Algorithm with Automatic Seeds Generation
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.