Parallel Universe Magazine - Issue 26, October 2016

Download
  • Arquivo:parallel-universe-issue-26.pdf
  • Tamanho:18.05 MB

Detalhes

Contents:

  • Letter from the Editor: What Will Machines Learn from You?, by Mike Lee
     
  • Modernize Your Code for Intel® Xeon Phi™ Processors, by Yolanda Chen and Udit Patidar
    Explore new Intel® Parallel Studio XE 2017 capabilities
     
  • Unleash the Power of Big Data Analytics and Machine Learning, by Vadim Pirogov, Ivan Kuzmin, and Sarah Knepper
    Solve big data era application challenges with Intel® Performance Libraries.
     
  • Overcome Python* Performance Barriers for Machine Learning, by Vasily Litvinov, Viktoriya Fedotova, Anton Malakhov, Aleksei Fedotov, Ruslan Israfilov, and Christopher Hogan
    Accelerate and optimize Python* machine learning applications.
     
  • Profiling Java* and Python* Code using Intel® VTune™ Amplifier, by Sukruv Hv
    Get more CPU capability for Java*- and Python*-based applications
     
  • Lightning-Fast R* Machine Learning Algorithms, by Zhang Zhang
    Get results with the Intel® Data Analytics Acceleration Library and the latest Intel® Xeon Phi™ processor
     
  • A Performance Library for Data Analytics and Machine Learning, by Shaojuan Zhu
    See how the Intel® Data Analytics Acceleration Library impacts C++ coding for handwritten digit recognition.
     
  • MeritData Speeds Up its Tempo* Big Data Platform Using Intel® High-Performance Libraries, by Jin Qiang, Ying Hu, and Ning Wang
    Case study finds performance improvements and potential for big data algorithms and visualization.

Para obter informações mais completas sobre otimizações do compilador, consulte nosso aviso de otimização.