Parallel Universe Magazine - Issue 26, October 2016

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



  • 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.

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