Biblioteca central de matemáticas Intel®

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
  • Avanzado
  • Principiante
  • Intermedio
  • Biblioteca central de matemáticas Intel®
  • Intel® Advanced Vector Extensions (Intel® AVX)
  • sgemm
  • DGEMM
  • Intel® AVX2
  • MKL PARDISO
  • Deep Neural Network extensions for Intel MKL

        Deep neural network (DNN) applications grow in importance in various areas including internet search engines, retail and medical imaging. Intel recognizes importance of these workloads and is developing software solutions to accelerate these applications on Intel Architecture that will become available in future versions of Intel® Math Kernel Library (Intel® MKL) and Intel® Data Analytics Acceleration Library (Intel® DAAL).

    While we are working on new functionality we published a series of articles demonstrating DNN optimizations with Caffe framework and AlexNet topology:

    Access violation for phase -1 of Pardiso

    I am using Pardiso and everything works well except one thing. I noticed that my application keeps increasing the memory usage when Pardiso is repeatedly called. I found in the documentation that I should use the phase -1 to release all internal memory. I am trying to do so, but I am getting a "forrtl: severe(157): Program Exception - access violation" error.

    I use the same call to Pardiso, just phase is changed to -1; is this wrong?

    Pardiso crashes with severe(172): Program Exception - access violation

    I am trying to use Pardiso, but it keeps crashing with the error message "forrtl: severe(172): Program Exception - access violation" in the console and with the error message "Access violation reading location 0xffffffffffffffff" in the dialog box in Visual Studio.

    This is how I use Pardiso:

    Parallel Studio 2017 Update 2 breaks MKL auto linking in Studio

    Automatic linking (in Visual Studio 2015 )of MKL is broken in Update 2.

    Previously if you selected MKL in Intel Performance Libraries the linker would get the MKL libraries automatically. I now have to add mkl_rt.lib to my linker options for all projects that use MKL . Curiously IPP and TBB link properly - they are not broken.

    Suscribirse a Biblioteca central de matemáticas Intel®