Participe do Intel IoT Roadshow 2015 - Sao Paulo

Nos dias 19 e 20 de Junho, vamos realizar em São Paulo, no Insper, a edição brasileira do Intel IoT Roadshow 2015, uma série de 20 eventos que serão realizados em diversos países, divulgando o kit para desenvolvimento de IoT da Intel.

Com o formato de hackathon, iremos utilizar no evento a placa Intel Edison e o Grove Starter Kit, em conjunto com o kit para desenvolvimento de IoT da Intel, um conjunto de softwares e bibliotecas Open Source que permitem o desenvolvimento de soluções utilizando a IDE do Arduino, Javascript (node.js), C/C++, Python e Scratch (via Wyliodrin).

Free developer software and training with Intel and iHub

Free developer software and training with Intel and iHub

In 2013, Intel began a long-term collaboration with one of the top innovation hubs in Sub Sahara, iHub. This collaboration has focused on enhancing the ability of developers to create rich user experiences on Intel®-based hardware

“The only definition of the iHub is ‘community’. Without the community, there is no iHub.”

Inconsistent Speedup


I'm new in using OpenMP. I would like to ask about speedup ratio.

I running C source code with OpenMP added with Intel core i5-2410M.

Based on my understanding, speedup = execution time of code using one thread/execution time of code using N threads 

The execution time recorded is time_diff in the attached code.

Basic OMP Parallelized Program Not Scaling As Expected

#include <iostream>
#include <vector>
#include <stdexcept>
#include <sstream>
#include <omp.h>

std::vector<int> col_sums(std::vector<std::vector<short>>& data) {
    unsigned int height = data.size(), width = data[0].size();
    std::vector<int> totalSums(width, 0), threadSums(width, 0);

    #pragma omp parallel firstprivate(threadSums)
        #pragma omp parallel for
        for (unsigned int i = 0; i < height; i++) {
  [0:width] += data[i].data()[0:width];

使用分层为英特尔® Galileo开发板创建Yocto镜像

本文介绍了如何从源代码为英特尔® Galileo 开发板(英特尔® 物联网开发人员套件的一部分)创建映像。 首先,需要获取编译映像需要使用的多个层。 您需要有足够大的磁盘空间 (~20GB),并且需要运行 最新的 64 位版 Linux* 操作系统。 我们在 Debian 7 和 openSUSE 12 上进行了尝试,希望其他系统上也能够运行。

该映像基于 poky 的 'daisy' 分支:
$ git clone --branch daisy git:// iotdk
$ cd iotdk

添加几个层 :
$ git clone git://
$ git clone --branch daisy git:// middleware
$ git clone git:// galileo

Promlems with Intel MPI

I have trouble with running Intel MPI on cluster with different different numbers of processors on nodes (12 and 32).

I use Intel MPI 4.0.3 and it works correctly on 20 nodes with 12 processors (Intel(Xeon(R)CPU X5650 @2.67)) at each, and all processors works correctly, then I try to run Intel MPI on other 3 nodes with 32 processors (Intel(Xeon(R)CPU E5-4620 v2@2.00) at each and they work correctly too.

Experten abonnieren