Article

Physical server provisioning with OpenStack*

This article explores the internal details of provisioning a physical machine using OpenStack*. Steps for setting up OpenStack are included, and no special hardware is required to begin use.

作者: Zhongyue Nah (Intel) 最后更新时间: 2019/07/06 - 16:40
博客

Intel's baremetal provisioning patch for DevStack

OpenStack employs DevStack for integration testing and development purposes.

作者: Zhongyue Nah (Intel) 最后更新时间: 2019/07/06 - 17:10
博客

Experimenting with OpenStack* Sahara* on Docker* Containers

Docker* is an emerging technology that has become very popular recently in the market. It provides a flexible architecture to deploy applications. OpenStack* is another hot technology on the market. It has been available for several years, became more stable and also added more features support in recent releases.
作者: WEITING C. (Intel) 最后更新时间: 2019/07/06 - 17:10
Article

Cloudera Hadoop* Single-Node Encryption Performance Case Study on Intel® Xeon® E5-2600 v3 Product Family

Cloudera software, specifically in its distributio

作者: 管理 最后更新时间: 2019/07/06 - 16:40
Article

Intel® Xeon® Processor E7 v3 Product Family

作者: Nguyen, Khang T (Intel) 最后更新时间: 2019/07/06 - 16:40
Article

Intel® Xeon® Processor E7 V3 Product Family New Reliability Features

1) Introduction
作者: Nguyen, Khang T (Intel) 最后更新时间: 2019/07/06 - 16:40
Article
Article

Intel® Xeon® Processor E7-8800/4800 V3 Product Family Technical Overview

Contents

1.     Executive Summary 2.     Introduction

作者: 最后更新时间: 2019/07/06 - 16:40
博客

The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease...
作者: David S. (Blackbelt) 最后更新时间: 2019/07/04 - 20:00
Article

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