Intel® Math Kernel Library

Intel® MKL 2018 Beta Update 1 is now available

Intel® MKL 2018 Beta is now available as part of the Parallel Studio XE 2018 Beta.

Check the Join the Intel® Parallel Studio XE 2018 Beta program post to learn how to join the Beta program, and the provide your feedback.

What's New in Intel® MKL 2018 Beta Update 1:

BLAS:

  • Addressed an early release buffer issue in threaded *GEMV
  • Improved TBB *GEMM performance for small m and n while k is large

DNN:

Announcing new open source project Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN)

Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN) is now available on the Github (https://github.com/01org/mkl-dnn) as an open source performance library for Deep Learning (DL) applications intended for acceleration of DL frameworks on Intel® architecture. Intel® MKL-DNN includes highly vectorized and threaded building blocks to implement convolutional neural networks (CNN) with C and C++ interfaces.

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
  • Advanced
  • Beginner
  • Intermediate
  • Intel® Math Kernel Library
  • Intel® Advanced Vector Extensions (Intel® AVX)
  • sgemm
  • DGEMM
  • Intel® AVX2
  • MKL PARDISO
  • Intel MKL DftiComputeForward how to get full transform matrix from CCE format in C

    I'm trying to implement a 2 dimensional fourier transform via use of MKL FFT functions.

    I'm interested in transforming from the space domain (i.e., my input signal is a 2D MxN matrix of `double`s) to the frequency domain (i.e., a 2D MxN output matrix of complexes with double accuracy, `MKL_Complex16`) and then back to the space domain after some filtering.

    how to deal with real and structurally symmetric matrix's parameters in PARDISO

    Hi

    I want to use  PARDISO to solve a problem, in which the matrix is real and structurally symmetric. I read the PARDISO Version 5.0.0  Reference Sheet — Fortran, and Parallel Sparse Direct Solver PARDISO | User Guide Version 5.0.0. I also lean some code which solve problem with symmetric or non-symmetric matrices. I know the parameter mtype need to be 1, since my matrix is real and structurally symmetric. But I do not know how to deal with other parameters.

    Any help would be appreciated.

    Regards, 
    rf.qian

    Struggling to get Automatic Off load working with MIC/MKL 2017

    I have a MIC card in a Microway XEON Workstation which seems to be functioning as expected (see micinfo debug output)

     

    After updating to MKL 2017 Update 3, I am struggling to set AO to function. I created a simple DGEMM test program and have been calling DGEMM with  square matrix sizes up to 16384, and cannot get AO to "kick-in".

    In prior versions of MKL, I could see AO working  at sizes of about 4096x4096 on this same machine.

    The following env vars are set.

    TR solver question

    When the solver returns RCI_Request = 2 to calculate the Jacobian, can I assume that x has not changed since the previous calculation of the function value?

    It would be a great performance boost if I could because my calculations of function value and jacobian are not seperable and I could just use my stored jacobian.

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