Xilinx enables machine learning from the edge to the cloud

BANGALORE, INDIA: At Embedded World, Xilinx announced expansion into a wide range of vision guided machine learning applications with the Xilinx reVISION stack.

“We are seeing tremendous interest in machine learning from the edge to the cloud, and believe that our ongoing investment in development stacks will accelerate mainstream adoption.” said Steve Glaser, SVP of Corporate Strategy at Xilinx.

The new reVISION stack enables a much broader set of software and systems engineers, with little or no hardware design expertise to develop intelligent vision guided systems easier and faster.  These engineers can now realize significant advantages when combining machine learning, computer vision, sensor fusion, and connectivity.

Developers with limited hardware expertise can use a C/C++/OpenCL development flow with industry-standard frameworks and libraries like Caffe and OpenCV to develop embedded vision applications on a single Zynq SoC or MPSoC.

reVISION is enabling a fast growing set of applications in markets where differentiation is critical, systems must be extremely responsive, and the latest algorithms and sensors need to be quickly deployed. This includes approximately two-thirds of the applications for vision focused semiconductors.

Applications span a number of markets such as high end consumer, automotive, industrial, medical, and aerospace & defense. Next generation applications include collaborative robots or ‘cobots’, ‘sense and avoid’ drones, augmented reality, autonomous vehicles, automated surveillance and medical diagnostics.

Leveraging the unique advantages of reconfigurability and any-to-any connectivity, developers can use the stack to rapidly develop and deploy upgrades. Reconfigurability is critical to ‘future proof’ intelligent vision-based systems as neural networks, algorithms, sensor technologies and interface standards continue to evolve at an accelerated pace.

“The embedded market is an evolving application space where changes in algorithms, neural networks and sensors require reconfigurability of the target platforms,” said Lakshmi Mandyam, senior director of segment marketing, ARM. “ARM-based Zynq technology from Xilinx will enable these applications to be deployed efficiently while accelerating the adoption of innovative machine learning applications from the edge to the cloud.”

The Xilinx reVISION stack includes a broad range of development resources for platform, algorithm and application development.