AI-Powered Layout Optimization in VLSI Design

Abstract

The Internet of Things (IoT) revolution has ushered in a new age of interconnected gadgets that significantly depend on artificial intelligence to enhance their performance. There has been a surge in interest about the development of low-power edge AI processors for IoT devices to meet the need for reduced power consumption in these devices. This paper examines the design techniques, challenges, and advancements in the development of such processors. The essay commences by emphasizing the need of low-power design for IoT devices, thereafter analyzing pertinent design variables such as system architecture, dataflow, and memory hierarchy. The many methods for reducing power consumption are examined, including power and clock gating, dynamic voltage/frequency scaling, and multi-core designs. This lecture will examine recent advancements in low-power VLSI design for edge AI processors, including heterogeneous-core processors and near-data processing. This study provides a comprehensive analysis of the latest concepts and methodologies for developing low-power VLSI edge AI processors for Internet of Things devices.