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Synopsys Demonstration of YOLO v2-based Object Detection and Identification

Jon Talbot, Field Applications Engineer in the Solutions Group at Synopsys, demonstrates the company’s latest embedded vision technologies and products at the February 2018 Embedded World conference. Specifically, Talbot demonstrates a YOLO (You Only Look Once) v2 CNN graph used for object detection and identification.

Deep learning inference is running on the combination of a DesignWare EV61 embedded vision processor core and a CNN880 neural network coprocessor core, both implemented on a Xilinx FPGA in Synopsys' HAPS-80 ASIC prototyping system. In the FPGA prototype, the Synopsys IP runs at 30 MHz, translating to ~1 fps (frame per second) inference performance. In a 16 nm-fabricated production ASIC, on the other hand, the cores are capable of running at between 800 MHz and 1.2 GHz.

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