Design and Implementation of Convolutional Neural Network Accelerator Based on RISCV

Internet of Things devices are faced with ever-increasing amounts of data, and they can no longer only do data collection as they did in the past, and hand over computing tasks to servers on the cloud. The growing computing requirements in the field of Internet of Things and the diversity of its scenarios put forward configurable and flexible customization requirements for customized processors. This paper conducts in-depth analysis and research on configurable customized processors, and analyzes related work in the field of RISC-V chips and deep convolutional neural networks in the field of device-side optimization at home and abroad. Based on this, this paper proposes an instruction and hardware design of a customizable deep convolutional neural network accelerator attached to Rocket-Chip Generator based on the RISC-V modular instruction set.