Join the Intel® Parallel Studio XE 2019 Beta Program today

Join the Intel® Parallel Studio XE 2019 Beta Program today

Join the Intel® IPP 2019 Beta and Intel® Parallel Studio XE 2019 Beta Program today and—for a limited time—get early access to new features and get an open invitation to tell us what you really think.

We want YOU to tell us what to improve so we can create high-quality software tools that meet your development needs.

Intel® IPP 2019 Beta is a component of Intel® Parallel Studio XE.  To get the package:
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New Features in Intel® IPP 2019 Beta

  • Added new functions to support the ZFP floating-point data compression and decompression. This release also introduces the optimization patch files for ZFP 0.5.2 source to provide drop-in optimization with the Intel® IPP functions.

  • Improved LZ4 compression and decompression performance on data with high entropy

    To learn more, visit Intel® IPP 2019 Beta release notes page.

Top New Features in Intel® Parallel Studio XE 2019 Beta

  • Scale and perform on the path to exascale. Enable greater scalability and improve latency with the latest Intel® MPI Library.
  • Get better answers with less overhead. Focus more fully on useful data, CPU utilization of physical cores, and more using new data-selection support from Intel® VTune Amplifier’s Application Performance Snapshot.
  • Visualize parallelism. Interactively build, validate, and visualize algorithms using Intel® Advisor’s Flow Graph Analyzer.
  • Stay up-to-date with the latest standards:
    • Expanded C++17 and Fortran 2018 support
    • Full OpenMP* 4.5 and expanded (partial) support for OpenMP* 5.0 (Preview 2) specification
    • Python* 3.6 and 2.7

To learn more, visit Intel® Parallel Studio XE 2019 Beta page.

Then sign up to get started.

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For more complete information about compiler optimizations, see our Optimization Notice.

I really hope you'll make the flags and integration of all Intel libraries easier.
For instance I'd be happy to have choices to create code path based on features and not Intel CPU.

Hopefully you'll also open source more of your packages (SVML would be great).

Also we really need a library optimized for small matrices like we used to have in IPP.

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