Open Source

Explore open source projects available, including installation guides and other learning material. We are continuously expanding our list of open source projects.

Optimized Frameworks

TensorFlow*

This Python*-based deep learning framework is designed for ease of use and extensibility on modern deep neural networks and has been optimized for use on Intel® Xeon® processors.

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Resources

MXNet*

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

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Resources

Intel® Optimization for Caffe*

The Intel® Optimization for Caffe* provides improved performance for of the most popular frameworks when running on Intel® Xeon® processors.

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Resources

Theano*

Theano*, a numerical computation library for Python, has been optimized for Intel® architecture and enables Intel® Math Kernel Library (Intel® MKL) functions.

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Resources

Intel® Optimization for Chainer*

Chainer* is a Python*-based deep learning framework for deep neural networks. Intel’s optimization for Chainer is integrated with the latest release of Intel® MKL-DNN.

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Software Libraries

nGraph™

nGraph™ is the first compiler that lets data scientists use their preferred deep learning framework on any number of hardware architectures, for both training and inference.

Intel® Open Sources Compute Library for Deep Neural Networks (clDNN)

clDNN is an open source performance library for deep learning applications that accelerates inference on Intel® Processor Graphics.

Intel® Machine Learning Scaling Library (Intel® MLSL)

Intel® Machine Learning Scaling Library (Intel® MLSL) provides efficient implementation of communication patterns used in deep learning.

Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel® Data Analytics Acceleration Library (Intel® DAAL) is a highly optimized library of computationally intensive routines for Intel® architecture-based platforms that helps speed big data analytics.

Intel® Distribution for Python

The Intel® Distribution for Python* speeds up core computational packages and optimizes performance with integrated libraries and parallelism techniques.

BigDL*

BigDL* is an open-source distributed deep learning library that can run directly on top of existing Intel® Xeon® processor-based Apache Spark* or Apache Hadoop* clusters. It leverages Intel® Math Kernel Library (Intel® MKL) to enable comprehensive support for deep learning on frameworks including Caffe* and Torch*.

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Research Projects

RL Coach

Reinforcement Learning Coach is an an open source research framework for training and evaluating reinforcement learning (RL) agents that uses the processing power of multi-core CPUs to enable efficient training of RL agents.

Distiller

Network compression can reduce the memory footprint of a neural network, increase its inference speed and save energy. Distiller provides a PyTorch environment for prototyping and analyzing compression algorithms, such as sparsity-inducing methods and low-precision arithmetic.

NLP Architect

NLP Architect is an open-source Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. It is intended to be a platform for future research and collaboration.

CARLA

CARLA is an open-source simulator for autonomous driving research that supports development, training, and validation of autonomous urban driving systems.

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