Xilinx has introduced its Kria programmable chips and boards for holding AI applications at the edge of the network. This should come in handy for visual applications like smarter cameras. San Jose, California-based Xilinx, which is in the process of being acquired by Advanced Micro Devices (AMD) for $35 billion, has a group of products dubbed the Kria portfolio of adaptive system-on-module offerings for AI at the edge. These are production-ready small form factor embedded boards that enable rapid deployment in edge-based applications. Coupled with a complete software stack and prebuilt, production-grade accelerated applications, Kria adaptive modules are a new method of bringing adaptive computing to AI and software developers.
The configurable, adaptable nature of FPGAs (Field Programmable Gate Arrays), as well system-on-chip architectures that employ them, make the technology invaluable in a multitude of applications, from AI-powered data centers to smart edge devices and the IoT. As part of its evolving strategy, Silicon Valley bellwether Xilinx has been integrating this adaptive technology into platform accelerator solutions for machine learning, as well as domain specific architecture solutions that incorporate various compute resources like ARM cores, high speed IO and even RF functions. One of the issues with modern heterogeneous compute architectures like this today, however, is that they're difficult for the average software developer to work with. You have to have a lot of hardware expertise to understand how to best utilize the various compute resources in modern systems, from CPUs to GPUs and FPGAs. However, today, Xilinx has announced a new, free, open source tool it calls Vitis.
Vision is one of the hottest area for AI development because vision can or will be used for a wide variety of consumer and industrial applications. Everything from security systems and retail monitoring solutions to manufacturing quality control and autonomous machines require vision AI. Xilinx has been developing chips and tools for AI development leveraging the company's expertise in programmable/adaptable platforms. Now, Xilinx is introducing the Kria System-on-Module (SoM) just for vision AI applications. A module or SoM is a predesigned system or sub-system with the required chips already mounted on a printed circuit board (PCB) that connect to other system components or interfaces.
The $199 Kria KV260 starter kit comes ready with inputs for mutiple cameras, image processing logic, and softare for object detection, to get people started easily on a computer vision product. In the hotly contested field of "edge" artificial intelligence, systems and chip makers are coming up with ways to get their customers to market without months or years of machine learning development. The latest contestant in that regard is programmable-logic maker Xilinx, which on Tuesday unveiled what is planned to be a family of "system-on-module," or SOM, products, chips on boards with pre-built applications for tasks such as object detection. The announcement features a starter kit for $199 containing all the guts of a camera system to detect people and things in the world. Kria, as the product line is called, are Xilinx's first production-ready SOMs.
At this week's Xilinx Developers Forum (XDF) in San Jose, California, Xilinx announced "Vitis" – a new framework for developing applications that use Xilinx programmable logic devices such as FPGAs, ACAPs, MPSoCs, RFSoCs, and all the other acronyms they can come up with that refer to what we'd call "FPGAs." With an abundance of grandiosity, the company proclaimed that Vitis was "five years and a total of 1,000 man-years in the making." We don't frequently encounter person-millenia metrics for new product announcements. Even if we assume that they started this in 1984 when Xilinx was founded, they would still have needed at least 28 engineers writing code full time for Vitis over that 35 year span. Spoiler: engineering-eons aside, Vitis IS impressive, and more importantly, is likely to mature to be even more impressive over the coming years.