Caffe* Training on Multi-node Distributed-memory Systems Based on Intel® Xeon® Processor E5 Family

Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
作者: Gennady F. (Blackbelt) 最后更新时间: 2019/07/05 - 14:54

OpenStack App Developer Survey

As part of a long-term commitment to enhance ease-of-use, the OpenStack UX project, with support of the OpenStack Foundation and the Technical Committee, is now bu

作者: Mike P. (Intel) 最后更新时间: 2017/06/07 - 12:14

Caffe* Optimized for Intel® Architecture: Applying Modern Code Techniques

This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
作者: 最后更新时间: 2019/07/06 - 16:40

Introducing DNN primitives in Intel® Math Kernel Library

Please notes: Deep Neural Network(DNN) component in MKL is deprecated since intel® MKL ​2019 and will be removed in the next intel® MKL Release.

作者: Vadim Pirogov (Intel) 最后更新时间: 2019/03/21 - 12:00

Open Source Project: Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel has created a data analytics acceleration project on github, to help accelerate data analytic

作者: James R. (Blackbelt) 最后更新时间: 2019/08/27 - 13:50