mkl 11.0

Intel MKL 11.1 Release Notes

This document provides a general summary of new features and important notes about the Intel® Math Kernel Library (Intel® MKL) software product.

Please see the following links to the online resources and documents for the latest information regarding Intel MKL:

  • Разработчики
  • Библиотека Intel® Math Kernel Library
  • mkl 11.0
  • mkl release notes
  • Образование
  • Webinar: Get Ready for Intel® Math Kernel Library on Intel® Xeon Phi™ Coprocessors

    Intel recently unveiled the new Intel® Xeon Phi™ product – a coprocessor based on the Intel® Many Integrated Core architecture. Intel® Math Kernel Library (Intel® MKL) 11.0 introduces high-performance and comprehensive math functionality support for the Intel® Xeon Phi™ coprocessor. You can download the audio recording of the webinar and the presentation slides from the links below.

  • Разработчики
  • Партнеры
  • Профессорский состав
  • Студенты
  • Linux*
  • Сервер
  • C/C++
  • Fortran
  • Начинающий
  • Intel® C++ Compiler
  • Intel® C++ Composer XE
  • Intel® Composer XE
  • Intel® Fortran Compiler
  • Intel® Fortran Composer XE
  • Intel® Parallel Composer
  • Библиотека Intel® Math Kernel Library
  • Intel® C++ Studio XE
  • Intel® Cluster Studio
  • Intel® Cluster Studio XE
  • Intel® Parallel Studio
  • Intel® Parallel Studio XE
  • Редакция Intel® Parallel Studio XE Composer
  • Редакция Intel® Parallel Studio XE Professional
  • Редакция Intel® Parallel Studio XE Cluster
  • Learning Lab
  • mkl 11.0
  • Intel Many Integrated Cores
  • Native and Offload Programming Models for Intel(R) MIC
  • Intel® Advanced Vector Extensions
  • Intel® Cluster Ready
  • Intel® Streaming SIMD Extensions
  • Инструменты для разработки
  • Intel® Many Integrated Core Architecture
  • Параллельные вычисления
  • Многопоточность
  • Векторизация
  • Webinar: Getting Reproducible Results with Intel® MKL 11.0

    Intel(R) MKL 11.0 introduces new functionality allowing users to balance the need for reproducible results with performance. The webinar recording and presentation linked below discusses the mechanisms that cause variability in floating point results, the new controls to limit these, and the performance trade-offs involved.

  • Разработчики
  • Профессорский состав
  • Студенты
  • Библиотека Intel® Math Kernel Library
  • mkl 11.0
  • cnr
  • MKL CNR
  • conditional numerical reproducibility
  • Conditional Numerical Reproducibility (CNR) in Intel MKL 11.0

    New functionality in Intel MKL 11.0 now allows you to balance performance with reproducible results by allowing greater flexibility in code path choice and by ensuring that algorithms are deterministic. To learn more about Conditional Numerical Reproducibility (CNR) see the following resources:

  • Библиотека Intel® Math Kernel Library
  • intel mkl
  • mkl 11.0
  • cnr
  • MKL CNR
  • conditional numerical reproducibility
  • intel math kernel library
  • Introduction to Conditional Numerical Reproducibility (CNR)

    Starting with 11.0 release,  Intel® MKL introduces a feature called Conditional Numerical Reproducibility (CNR) which provides functions for obtaining reproducible floating-point results when calling library functions from their application.  When using these new features, Intel MKL functions are designed to return the same floating-point results from run-to-run, subject to the following limitations:

  • Разработчики
  • Средний
  • Библиотека Intel® Math Kernel Library
  • mkl 11.0
  • cnr
  • MKL CNR
  • MKL reproducible results
  • consistent results in MKL
  • MKL Conditional Numerical Reproducibility
  • Инструменты для разработки
  • Introduction to the New Functions Providing Bitwise Reproducibility

    Intel MKL 11.0 will introduce new functions which will increase those cases where bitwise reproducible results can be achieved and with as little sacrifice in performance as possible.
  • Библиотека Intel® Math Kernel Library
  • mkl 11.0
  • cbwr
  • MKL CBWR
  • MKL reproduciable results
  • MKL Conditional Bitwise Reproducibility
  • Оптимизация
  • Подписаться на mkl 11.0