Understanding the corner cases of Vectorization Intensity

Correct performance analysis of an application is absolutely vital to optimize the performance on any architecture. A previous article describes several metrics recommended for a basic analysis of your application on the Intel® Xeon Phi™ coprocessor.

  • Développeurs
  • Professeurs
  • Étudiants
  • Avancé
  • Intel® VTune™ Amplifier
  • vtune
  • MIC
  • Advanced Xeon Phi
  • Xeon Phi
  • Tuning
  • optimization
  • Modernisation du code
  • Intel® Many Integrated Core Architecture
  • Tips and Tricks to Optimize Android Apps on x86

    Intel has a vested interest in helping developers provide Android applications that run well (or even best) on Intel architecture. While Intel is working at the community level - optimizing Dalvik Java, V8 engine, and Bionic C; contributing to the code base; and providing releases with both 32 bit and 64-bit Kernels for IA; they are also creating new tools to help  Android developers. Many of these focus on improving performance beyond that available with the default ARM translation layer for x86: libhoudini

    Introduction to Parallel Programming video lecture series – Part 01 “Why Parallel? Why Now?”

    The lecture given here is the first part in the “Introduction to Parallel Programming” video series. This part endeavors to define parallel computing, explain why parallel computing is becoming mainstream, and explain why explicit parallel programming is necessary. This part sets the tone for the other 11 parts in the series.

    Running time: 9:51

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