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Intel® Parallel Studio XE 2017 Update 2 Readme

Deliver top application performance and reliability with Intel® Parallel Studio XE 2017. This C++ and Fortran software development suite simplifies the design, build, debug, and tune of applications that take advantage of scalable MPI, thread and vector parallel processing to boost application performance.
  • Apple macOS*
  • Linux*
  • Microsoft Windows* 10
  • Microsoft Windows* 8.x
  • C/C++
  • Fortran
  • Python*
  • Intel® Parallel Studio XE
  • Intel® Parallel Studio XE Composer Edition
  • Intel® Parallel Studio XE Professional Edition
  • Intel® Parallel Studio XE Cluster Edition
  • Intel® Distribution for Python 2017 Update 2 Readme

    Intel® Distribution for Python powered by Anaconda gives you ready access to tools and techniques for high performance to supercharge all your Python applications on modern Intel platforms. Whether you are a seasoned high-performance developer or a data scientist looking to speed up your workflows, the Intel Distribution for Python powered by Anaconda delivers an easy-to-install, performance-optimized Python experience to meet even your most demanding requirements.

  • Apple macOS*
  • Linux*
  • Microsoft Windows* 10
  • Microsoft Windows* 8.x
  • Python*
  • Intel® Parallel Studio XE
  • Intel® Distribution for Python*
  • BigDL:一种面向 Apache Spark 的分布式深度学习库

    As the leading framework for Distributed ML, the addition of deep learning to the super-popular Spark framework is important, because it allows Spark developers to perform a wide range of data analysis tasks—including data wrangling, interactive queries, and stream processing—within a single framework. Three important features offered by BigDL are rich deep learning support, High Single Node Xeon Performance, and Efficient scale-out leveraging Spark architecture.
  • Artificial Intelligence
  • Code Samples
  • Big Data
  • Machine Learning
  • BigDL: Distributed Deep Learning on Apache Spark*

    As the leading framework for Distributed ML, the addition of deep learning to the super-popular Spark framework is important, because it allows Spark developers to perform a wide range of data analysis tasks—including data wrangling, interactive queries, and stream processing—within a single framework. Three important features offered by BigDL are rich deep learning support, High Single Node Xeon Performance, and Efficient scale-out leveraging Spark architecture.
  • Artificial Intelligence
  • Code Samples
  • Big Data
  • Machine Learning
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