ZTE achieves deep learning benchmark via Intel FPGA

ZTE achieves a record–beyond a thousand images per second in facial recognition–known as “theoretical high accuracy” for its custom topology. Deep learning technology is very important as it can enable perception in mobile edge computing systems. Hence, ZTE has collaborated with Intel to reach a benchmark in deep learning and convolutional neural networks (CNN). The technology is what many companies in Internet search and AI are trying to advance, and includes picture search and matching, as one example. The test took place in Nanjing City, China, where ZTE’s engineers used Intel’s midrange Arria 10 FPGA for a cloud inferencing application using a CNN algorithm. ZTE has achieved a record–beyond a thousand images per second in facial recognition–known as “theoretical high accuracy” for its’ custom topology. Intel’s Arria 10 FPGA accelerated…


Link to Full Article: ZTE achieves deep learning benchmark via Intel FPGA

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