基于英特尔® 至强 E5 系列处理器的单节点 Caffe 评分和训练

As Deep Neural Network (DNN) applications grow in importance in various areas including internet search engines and medical imaging, Intel teams are working on software solutions to accelerate these workloads that will become available in future versions of Intel® Math Kernel Library (Intel® MKL) and Intel® Data Analytics Acceleration Library (Intel® DAAL). This technical preview demonstrates...
Authored by Gennady F. (Blackbelt) Last updated on 03/11/2019 - 13:17

安装英特尔® Theano*软件优化包和支持工具

Theano* is a Python* library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays. Theano can be installed and used with several combinations of development tools and libraries on a variety of platforms. This tutorial provides one such recipe describing steps to build and install Intel-optimized Theano with Intel®...
Authored by Sunny G. (Intel) Last updated on 05/08/2018 - 10:50

英特尔® MKL-DNN:第一部分 – 库的概述和安装

英特尔 MKL-DNN 教程系列的开发人员简介从开发人员的角度介绍了英特尔 MKL-DNN。第一部分提供了丰富的资源,详细介绍了如何安装和构建库组件。
Authored by Bryan B. (Intel) Last updated on 05/08/2018 - 10:50

英特尔® MKL-DNN:第二部分 – 代码示例创建与详解

在本篇中 (系列教程第二部分),将介绍如何配置集成开发环境 (IDE),以创建 C++ 代码示例,并提供基于 AlexNet* 深度学习拓扑的代码详解。
Authored by Bryan B. (Intel) Last updated on 05/23/2018 - 11:00
Blog post

英特尔和 Facebook* 共同协作,在英特尔 CPU 上提高 Caffe2 的性能


Authored by Andres Rodriguez (Intel) Last updated on 05/08/2018 - 09:38

最大限度提升 CPU 上的 TensorFlow* 性能:推理工作负载的注意事项和建议

本文将介绍使用面向 TensorFlow 的英特尔® 优化* 进行 CPU 推理的性能注意事项
Authored by Nathan Greeneltch (Intel) Last updated on 08/09/2019 - 02:02

面向英特尔® 架构优化的 Caffe*:使用现代代码技巧

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.
Authored by Last updated on 10/15/2019 - 16:50