Código abierto

Introduzione allo sviluppo di applicazioni mobile cross-platform

Lo sapevi che si possono sviluppare applicazioni mobile cross-platform di elevata qualità utilizzando solo HTML, CSS e JavaScript ? Ok, domanda banale, molti oramai lo sanno ma tantissimi developers non ne sono ancora al corrente o, sono ancora scettici o comunque non ancora del tutto convinti riguardo l’uso di queste tecnologie in ambito mobile; proprio per quest’ultimo motivo ho deciso di scrivere una serie di blog posts ed alcuni articoli tecnici che verranno linkati man mano in calce a questo blog post per, mostrarti come con l’uso delle tue skills in ambito web e, con l’IDE Intel XDK si possano sviluppare applicazioni mobile di elevata qualità in maniera veloce ed infine estremamente efficiente.

Ubuntu 15.04 Provides Openstack Kilo Preinstalled for Easier Deployments on ONP Servers

The folks here at Intel see me as a bit of an Ubuntu fanboy.  For the most part, I spend a lot of time in the lab working on the ONP Server using CentOS.   For me, it is less about being an Ubuntu fan and more about using a platform that is easier choice for Openstack developers.    I recently had an opportunity to peel off an extra ONP Server and install the new Ubuntu 15.04 to have a look.  

Intel® RealSense™ made easy with SharpSenses

Many developers worldwide are taking advantage of the Intel® RealSense™  technologies to create really amazing applications with a whole new dimension for user interaction.

Intel® provides an SDK that exposes all the features of the R200 and F200 cameras. The SDK is very powerful but it requires some time to find your way into it. To help people to get up and running with just a few lines of code I started SharpSenses.

  • Desarrolladores
  • Profesores
  • Estudiantes
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 10
  • Microsoft Windows* 8.x
  • Tecnología Intel® RealSense™
  • Windows*
  • .NET*
  • C#
  • Principiante
  • SDK de Intel® RealSense™
  • RealSense
  • sharpsenses
  • c#
  • windows
  • F200
  • opensource
  • Tecnología Intel® RealSense™
  • Microsoft Windows* 8 Desktop
  • Código abierto
  • OpenMP Shared Arrays

    I have two questions about WRITE/READ operations on shared arrays.
     1) In my program I write a different element of a given shared array at every iteration of an OpenMP-parallelized DO LOOP. The results that I get should be right but I'm just wondering whether this is fine or I should enclose the READ/WRITE section in a CRITICAL block. Then, I also READ elements from a shared array without modifying them and it seems to work. Are these procedures correct?

    [Bug] OSX Yosemite 10.10 fails when compiling

    # ProductName:    Mac OS X
    # ProductVersion:    10.10.3
    # BuildVersion:    14D136

    curl -O https://www.openmprtl.org/sites/default/files/libomp_20150401_oss.tgz
    gunzip -c libomp_20150401_oss.tgz | tar xopf -
    cd libomp_oss

    in line 124..126 of libomp_oss/src/makefile.mk:
    ifeq "$(os)" "mac"
        mac_os_new := $(shell /bin/sh -c 'if ; then echo "1"; else echo "0"; fi')

    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.

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