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Deep Learning on an Intel Processor with MKL-DNN

Ram Cherukuri, MathWorks

Learn how you can generate code from a trained deep neural network in MATLAB® for Intel® processors that support the Advanced Vector Extension 2 (AVX2) instruction set like the Intel Xeon family of processors. Pedestrian detection is used as the deep learning application example and the generated code is deployed on an Intel Xeon processor. 

The generated code leverages the Intel MKL-DNN library, which is an open source performance library for deep learning applications, providing vectorized and threaded building blocks optimized for Intel architectures. The neural network for pedestrian detection is shown running on an Intel Xeon E5 v3 processor at about 30 fps.

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Pedestrian Detection Example
Intel MKL-DNN Library
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