整理您的数据和代码: 优化和内存 — 第 1 部分

This series of two articles discusses how data and memory layout affect performance and suggests specific steps to improve software performance. The basic steps shown in these two articles can yield significant performance gains. These two articles are designed at an intermediate level. It is assumed the reader desires to optimize software performance using common C, C++ and Fortran* programming...
作者: David M. 最后更新时间: 2017/06/07 - 10:52

使用英特尔® SSSE3 指令集在本地语音识别中加速 DNN 算法

The main algorithm of speech recognition has changed to DNN (Deep Neural Network). Without internet, the speech recognition service in your mobile devices nearly useless, very few times it can listen to what you said and work.With support for the SSSE3 instruction set on Intel’s CPU, we could easy run a DNN based speech recognition application without the internet. Adding direct SSSE3 support...
作者: Wenyan L. (Intel) 最后更新时间: 2017/02/24 - 12:39

基于 X86 的 Jack (Java* Android* 编译器套件) 和 Jill (Jack 中间库链接)

Jack (Java* Android* Compiler Kit) is a new Google* tool that includes a compiler from Java source code to the Android dex file format. Jack has its own .jack library and provides most toolchain features as part of a single tool: repackaging, shrinking, obfuscation and multidex. There is also a tool that translates existing .jar files to the .jack library format.
作者: DENIS S. (Intel) 最后更新时间: 2017/12/14 - 15:08

案例研究 - 利用英特尔® 深度学习 SDK 训练图像识别模型

本篇案例研究不仅介绍了 LeNet*(一种进行手写数字识别的重要图像识别拓扑),还展示了如何利用训练工具在面向英特尔® 架构优化的 Caffe* 上对混合国家标准技术研究所 (MNIST) 数据集进行可视化设置、调试和训练。目标受众是数据科学家。
作者: Meghana R. (Intel) 最后更新时间: 2017/08/10 - 00:49


作者: 最后更新时间: 2017/06/14 - 16:52


4.2 常用的编译器选项

4.2.1 选用编译器选项的基本步骤


作者: Jiong Z. (Intel) 最后更新时间: 2017/06/14 - 13:23

借助针对英特尔® 架构优化的 Caffe* 管理深度学习网络

如何面向英特尔® 架构优化 Caffe*,训练深度网络模型及部署网络。
作者: Andres R. (Intel) 最后更新时间: 2017/08/25 - 01:15