Intel Vision Accelerator Solutions Speed Deep Learning and AI on Edge Devices

November 5, 2018 Rich Nass

Intel recently unveiled its family of Vision Accelerator Design Products aimed at artificial intelligence (AI) inference and analytics performance on Edge devices, where data originate and are acted upon. The products come in two forms: one that features an array of Intel Movidius vision processors and one built on the company’s Arria 10 FPGA. The solutions build on the OpenVINO software toolkit that potentially improves neural network performance on various Intel products and gets developers closer to the goal of cost-effective, real-time image analysis and intelligence within their IoT devices.

Intel Vision Accelerator Design Products offload AI inference workloads to purpose-built accelerator cards, also based on Intel products. The deep-learning inference accelerators scale based on the needs of the specific application. Hence, the AI applications could be running in the data center, in on-premise servers, or inside Edge devices. With the OpenVINO toolkit, developers can easily extend their investment in deep learning inference applications on Intel CPUs and integrated GPUs to these new accelerator designs, saving time and money.

About the Author

Rich Nass

Richard Nass is the Executive Vice-President of OpenSystems Media. His key responsibilities include setting the direction for all aspects of OpenSystems Media’s Embedded and IoT product portfolios, including web sites, e-newsletters, print and digital magazines, and various other digital and print activities. He was instrumental in developing the company's on-line educational portal, Embedded University. Previously, Nass was the Brand Director for UBM’s award-winning Design News property. Prior to that, he led the content team for UBM Canon’s Medical Devices Group, as well all custom properties and events in the U.S., Europe, and Asia. Nass has been in the engineering OEM industry for more than 25 years. In prior stints, he led the Content Team at EE Times, handling the Embedded and Custom groups and the TechOnline DesignLine network of design engineering web sites. Nass holds a BSEE degree from the New Jersey Institute of Technology.

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