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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

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  • 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.

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  • Introduction to the Intel MKL Extended Eigensolver

    Intel® MKL 11.0 Update 2 introduced a new component called Extended Eigensolver routines. These routines solve standard and generalized Eigenvalue problems for symmetric/Hermitian and symmetric/Hermitian positive definite sparse matrices. Specifically, these routines computes all the Eigenvalues and the corresponding Eigenvectors within a given search interval [λmin, λmax]:

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  • 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:

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