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The Intel® Math Kernel Library Sparse Matrix Vector Multiply Format Prototype Package

 

This article describes the new features in the Intel® Math Kernel Library Sparse Matrix Vector Multiply Format Prototype Package (Intel® MKL SpMV Format Prototype Package) for use on the Intel® Xeon Phi™ coprocessor. The package includes a new two-stage API for select SpMV operations as well as support for the ELLPACK Sparse Block (ESB) format.

Introduction

  • Разработчики
  • Профессорский состав
  • Студенты
  • Linux*
  • C/C++
  • Fortran
  • Продвинутый
  • Средний
  • OpenMP*
  • Advanced Xeon Phi
  • intel mkl
  • Sparse Matrix-Vector multiplication
  • csr format
  • Ellpack Sparse Block format
  • Intel(R) Math Kernel Library v.11.1 - the new Install Option

     Intel® Math Kernel Library contains many different components which support several target platforms, programming languages, threading models etc.  In the previous versions on MKL, users installed all of these components as there was no option to ignore the components they do not need.

    In the latest version of Intel® MKL ( v.11.1 )  there is a new installation option which allows a user  to select the list of components he/she will need and install only these ones.

  • Разработчики
  • Студенты
  • Apple OS X*
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 8
  • Unix*
  • C/C++
  • Fortran
  • Начинающий
  • Библиотека Intel® Math Kernel Library
  • intel mkl
  • installation
  • 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
  • Подписаться на intel mkl