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        Aaware Far Field Voice Development Platform: Powered by Xilinx – Demo Shorts

        This development platform provides a configurable microphone array (up to 13 mics) with best in class sound capture coupled with a complete Ubuntu embedded software development environment, making it instantly software ready. Aaware uses adaptive algorithms and accelerates performance leveraging the power of the Xilinx Zynq SoC.

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        Swift Navigation Centimeter-Accurate GPS Positioning for Autonomous Vehicles: Powered by Xilinx

        Swift Navigation offers highly precise, centimeter-accurate GPS positioning technology, such as the Piksi Multi multi-band, multi-constellation GNSS receiver for autonomous vehicles. Xilinx enables Swift Navigation to build better systems faster and rapidly deploy in-field updates through the reconfigurability of Zynq SoCs.

        Zynq Ultrascale+ delivers Deterministic Processing for Mixed Criticality Applications in Industrial, Automotive, and Aviation Markets

        Today’s market requirements are forcing increased computational requirements across all embedded applications through the use of multi-core SoCs, while simultaneously requiring the preservation of legacy real-time code often developed decades ago for single core processors. Often, the performance limitations of real-time processors lead designers to consider and use application processors to achieve desired performance at expense of determinism and worst case execution time (WCET).

        Xilinx Accelerates Industrial IoT Solutions with AWS IoT

        This webinar will provide an overview of the Xilinx and AWS IoT respective technology stacks and how the companies have worked together to provide integrated reference designs that customers can use to jumpstart their Industrial IoT (IIoT) solution. The presenters will reference a functioning Xilinx with AWS IoT enabled distributed control application example that leverages the scale of AWS Cloud application provisioning, system dashboards, secure cloud communications, and FPGA based machine learning on top of Xilinx Zynq UltraScale+ and Zynq 7000 system on chip (SoC) hardware platforms. Specifically, the reference designs will show how AWS IoT Greengrass can be integrated on a Zynq UltraScale+ device to deploy FPGA based edge machine learning inference functions using Xilinx PYNQ and ML Suite technology. The reference design also includes Amazon FreeRTOS on a Zynq7000 device to establish secure telemetry and control state information communication from the extreme edge of the system to the AWS Cloud. Lastly the workshop will point attendees to relevant Xilinx reference platforms and the relevant public Xilinx on AWS IoT GitHub sites with instructions, SD card images, and AWS configuration scripts so that attendees can see the examples in action themselves.

        Accelerating Predictive Maintencance with Python and Neural Network-Based Edge AI

        Subtle changes in performance or behavior of critical assets in factories, hospitals, and other environments can be identified by machines much earlier than a human. Xilinx powered systems can incorporate intelligence to maximize productivity and lower downtime by applying predictive maintenance. Xilinx’s Python and Neural Network-based Edge AI Solutions simplify the implementation of hardware accelerated predictive maintenance to continuously monitor assets, analyze data, and intelligently plan service for these systems. In this webinar, you will see how this is done on an Industrial Motor and go beyond!

        EV Motor Control System Demo

        The demand for SiC (Silicon Carbide) is increasing in the development of electric vehicle (EV) motors because of its ability to reduce weight and drive EV motors faster. OnSemi’s Universal Controller Board (UCB) solution, containing the adaptable Zynq®-7000 SoC, guarantees deterministic and fast control loops to take advantage of the high switching frequencies that SiC enables. In the dedicated programmable logic of the adaptable Zynq-7000 SoC, accurate control of high-speed motors is achieved – displaying high performance and high efficiency.