Biblioteca kernel de matemática Intel®

Announcing new tool -- Intel® Math Kernel Library LAPACK Function Finding Advisor

The Intel® Math Kernel Library (Intel® MKL) LAPACK domain contains a huge variety of routines. Now, a new tool is provided with a faster method of finding appropriate LAPACK functions in Intel® Math Kernel Library Developer Reference document. This tool would be very useful for Intel® MKL newbies and for users not familiar with LAPACK function naming conventions. By using this tool, users can specify functionality as parameters in drop down lists, descriptions of all functions satisfying the requirements will be shown through this tool. 

Intel® MKL 11.3.3 patch

There are two listed below limitations with Intel® Math Kernel Library (Intel® MKL) 11.3 Update 3 which were discovered recently. The official fix of these issues will be available the nearest update Intel MKL 11.3.4.

If you require an immediate Intel MKL update to address these issues, please submit a ticket at Intel Premier Support (https://premier.intel.com) for the Intel MKL product.

Known Limitations: 

  • FreeBSD*
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 10
  • Microsoft Windows* 8.x
  • Unix*
  • Fortran
  • Avançado
  • Principiante
  • Intermediário
  • Biblioteca kernel de matemática Intel®
  • Intel® Advanced Vector Extensions (Intel® AVX)
  • sgemm
  • DGEMM
  • Intel® AVX2
  • MKL PARDISO
  • MKL License

    Hi,

    I registered for the free Intel Performance Libraries. As far as I understood the Intel Simplified Software License these products can be used commercially. But when I have a look at https://registrationcenter.intel.com/en/products/ the license type is noncommercial.

    So...can these products be used commercially or did I make a mistake during registration ?

     

    Using Pardiso to solve linear system with the same pattern

    Suppose that I need to solve a linear system in this form, Ax=b, in many iterations. In each iteration, I get a new matrix A. However, the pattern of the matrix is the same. That is, the indices of the nonzeros in A are the same throughout the iterations, but the values of the nonzeros change throughout the iterations. 

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