Огляд пристрою KRIA KV260 VISION AI для інтелектуального машинного бачення

Abstract

Deep Learning (DL) has revolutionized research and development. A couple of problems are that DL requires a lot of power and can be slow. Programmable gate arrays (FPGAs) are excellent candidates for implementing DL algorithms and solutions because they are configurable and offer low latency and low power consumption. Additionally, the versatile FPGA architecture allows users to design application-specific hardware instead of using general-purpose hardware in the processor. An example of these solutions is the Xilinx Kria KV260 Vision AI (KV260) FPGA board. This board contains numerous accelerated programs for performing DL using live camera feed.