Xilinx Kria Platform Brings Adaptive AI Acceleration To The Masses At The Edge

Silicon Valley adaptive computing bellwether Xilinx announced its entrance into the growing system-on-module (SOM) market today, with a portfolio of palm-sized compute modules for embedded applications that accelerate AI, machine learning and vision at the edge. Xilinx Kria will eventually expand into a family of single board computers based on reconfigurable FPGA (Field Programmable Gate Array) technology, coupled to Arm core CPU engines and a full software stack with an app store, the first of which is specifically is targeted at AI machine vision and inference applications. The Xilinx Kria K26 SOM employs the company's UltraScale multi-processor system on a chip (MPSoC) architecture, which sports a quad-core Arm Cortex A53 CPU, along with over 250 thousand logic cells and an H.264/265 video compression / decompression engine (CODEC). This may sound like alphabet soup as I spit out acronyms, however, the underlying solution is a compelling offering for developers and engineers looking to give new intelligent systems, in industries like security, smart cities, retail analytics, autonomous machines and robotics, the ability to see, infer information and adapt to their deployments in the field. Also on board the Xilinx Kria K26 SOM is 4GB of DDR4 memory and 245 general purpose IO, along with the ability to support 15 cameras, up to 40 Gbps of combined Ethernet throughput, and four USB 2/3 compatible ports.