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Machine learning is being applied to many new applications, from voice recognition to vision processing. One of the hottest applications is in the quest for self-driving cars. As researchers push machine learning to solve bigger problems, they are often limited by the performance of today’s processors. Achieving the performance needed for large neural networks requiring highly optimized hardware design. New architectures and new chip designs will revolutionize future products in this rapidly evolving field. To better prepare for the challenges in autonomous design, we have created a new conference. Join us on April 6, 2017 when we host the first Linley Autonomous Hardware Conference.
Future autonomous hardware platforms will use diverse vision-processing hardware such as DSPs, GPUs, CPUs, and proprietary application-specific hardware. OpenVX is an industry-standard Computer Vision API designed for efficient implementation on a variety of embedded platforms. Cadence has developed an implementation of the OpenVX API that runs on the Tensilica Vision DSP products. This talk will provide an overview of the API and its benefits, and an overview of the Cadence implementation and the performance and time-to-market advantages it provides for autonomous hardware platforms. The talk will also summarize future extensions OpenVX will have for neural networks and safety-critical applications.
The Embedded Vision Alliance is a media sponsor of this event. Learn more about the Embedded Vision Summit.