Low-power FPGA accelerates embedded vision: Page 2 of 2

July 15, 2019 //By Julien Happich
embedded vision
With its Smart Embedded Vision initiative, Microchip aims to provide solutions for designing intelligent machine vision systems based on low-power PolarFire FPGAs.

Last but not least, the Smart Embedded Vision partners ecosystem has been extended with the introduction of Kaya Instruments, which provides PolarFire FPGA IP Cores for CoaXPress v2.0 and 10 GigE vision, to Microchip’s partner ecosystem. The ecosystem also includes Alma Technology, Bitec and artificial intelligence partner ASIC Design Services, which provides a Core Deep Learning (CDL) framework that enables a power-efficient Convolutional Neural Network (CNN)-based imaging and video platform for embedded and edge computing applications.

With family members ranging from 100K to 500K Logic Elements (Les), the PolarFire FPGAs offer 30 to 50 percent lower total power over competing Static Random-Access Memory (SRAM)-based mid-range FPGAs, claims the manufacturer. Microchip has also unveiled a new MIPI-CSI2-based machine learning camera reference design for smart embedded system implementations. Based on the PolarFire FPGA imaging and video kit that uses inference algorithms from Microchip partner ASIC Design Services, the reference design is free for customers to evaluate.

Microchip Technology – www.microchip.com


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