Framework Optimizations

Faster training of deep neural networks on Intel® Architecture

Achieve faster training of deep neural networks on a robust, scalable infrastructure.


Intel®'s innovation and reference deep learning framework committed to best performance on all hardware.

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Intel and Google engineers have been working together to optimize TensorFlow, a flexible open-source AI framework, for Intel® Xeon® and Intel® Xeon Phi™ processors.

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Installation Documentation


The Berkeley Vision and Learning Center (BVLC) has made the Intel® Distribution of Caffe* an available branch off of their mainline. Intel has contributed to one of the most popular frameworks for image recognition by improving Caffe* performance when running on Intel® Xeon® processors and Intel® Xeon Phi™.

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Installation Documentation


This fork of the very popular Python* library, Theano, improves performance on CPU devices, in particular Intel® Xeon® processors and Intel® Xeon Phi™

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Installation Documentation


The open-source, deep learning framework MXNet* includes built-in support for the Intel® Math Kernel Library (Intel® MKL). This includes optimizations for Intel® Advanced Vector Extensions 2 (Intel® AVX2) and Intel® Advanced Vector Extension 512 (Intel® AVX-512) instructions, which are supported in Intel® Xeon® and Intel® Xeon Phi™ processors.

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Installation Documentation


BigDL is an open source distributed deep Learning framework for Apache Spark. It brings native support for deep learning functionalities to Spark with single node Xeon performance, and efficiently scales out deep learning workloads based on the Spark architecture

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Installation Documentation

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