Recipe: Optimized Caffe* for Deep Learning on Intel® Xeon Phi™ processor x200

Overview The computer learning code Caffe* has been optimized for Intel® Xeon Phi™ processors. This article provides detailed instructions on how to compile and run this Caffe* optimized for Intel® architecture to obtain the best performance on Intel Xeon Phi processors. Introduction Caffe is a popular open source deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and community contributors. Together with AlexNet, a neural network topology for image recognition, and ImageNet, a database of labeled images, Caffe is often used as a benchmark in the domain of image classification. An Intel version of BVLC Caffe, referred to as Caffe optimized for Intel architecture in the rest of this article, has been created to optimize the framework performance for Intel architectures. These optimizations are available on Github…


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