Overview | Deep Learning SDK

Intel® Deep Learning SDK

Tools to accelerate deep learning training and deployment

  • Visually set up, tune, and run deep learning algorithms
  • Unleash inference performance on deep learning deployment
  • Simplify installation of popular deep learning frameworks, optimized for Intel platforms

What is the Intel® Deep Learning SDK?

The Intel® Deep Learning SDK is a free set of tools for data scientists and software developers to develop, train, and deploy deep learning solutions. The SDK encompasses a training tool and a deployment tool that can be used separately or together in a complete deep learning workflow.

Training Tool

  • Easily prepare training data, design models, and train models with automated experiments and advanced visualizations
  • Simplify the installation and usage of popular deep learning frameworks optimized for Intel platforms

Data scientists are the primary users.

Deployment Tool

  • Optimize trained deep learning models through model compression and weight quantization, which are tailored to end-point device characteristics
  • Deliver a unified API to integrate the inference with application logic

Application developers are the primary users.

What's New

  • The beta release of the training tool and deployment tool that supports Intel® Distribution for Caffe* is now available. For more information, see the Download Center.
  • The training tool for image classification includes many advanced features such as custom networks (topologies) for model creation, integration with interactive notebooks, and the ability to install on OS X* or Amazon Web Services (AWS)*.
  • The deployment tool supports image classification and image segmentation use cases with inference on floating point 32 bit precision (FP32).

Release Notes

Technical Specifications

Training Tool:

Required Hardware Optimized for Intel® Xeon® processor, Intel® Xeon Phi™ processor, and Intel® Core™ i7 processor Extreme Edition
Required OS Ubuntu* 14.04 or higher (64 bit)
CentOS* 7 (64 bit)
Mac OS* 10.11 or higher (64 bit)
Supported Browser Google Chrome*
Supported Use Cases Image classification

Deployment Tool:

Required Hardware Optimized for Intel® Xeon® and Intel® Core™ processors
Required OS Development Environment: Ubuntu 14.04, 16.04 (64 bit)
Target Inference Platform: Ubuntu 14.04 (64 bit)
Supported Use Cases Image classification and image segmentation
Supported Layers Convolution, deconvolution, fully connected, pooling, rectified linear unit (RelU), softmax, eltwise, crop, local response normalization (LRN), concatenation, power, and split