Intel® Integrated Performance Primitives

Intel® IPP example code for Intel® System Studio 2016 Beta Update 1

Intel® Integrated Performance Primitives (Intel® IPP) provides the following examples in Intel® System Studio packages: 

  • Custom Dynamic Library Example
  • Multi-thread Image Resize Example: ipp_resize_mt
  • Image Linear Transform Example: ipp_fft
  • External Threading Example: ipp_thread    

The example code is installed at <Install Dir>\ipp\examples folder.

  • Intel® System Studio, редакция&nbsp;Professional
  • Intel® Integrated Performance Primitives
  • Лицензионное соглашение: 

    IPP multi-threaded libraries are not installed - static link


    my error is 

    ...v110\ImportBefore\Intel.Libs.IPP.v110.targets(92,5): error : IPP multi-threaded libraries are not installed.

    i have one computer which I compiled a project with IPP. and linked the lib which is created from this project with another project. on this computer I have Intel parallel studio 2015 installed.

    my goal is to link the IPP project into the other project without having to install IPP for all the the other developers on my team.

    the error i'm getting is that probably IPP is not installed on the other computer.

    Problem while replacing old ippiResizeCenter method with ippiResize<interpolation> method


      We were using the resizeCenter method in our software which takes parameters to scaleX & scaleY and offsets in X & Y directions .

      Now we want to upgrade the software to 8.2 where this method is totally removed.

      I saw the resizeCubic method but this method doesn't take the scale in X & Y directions and also offset.

      But the new method considers only the ROI's of source and destination. 

      I really doesn't understand the concept behind the new resizeCubic method ,that how we can scale down/ up the source raster to fit  inside the

    EigenValuesVectors - two matrices/complex values


    I really need to implement into C++ code calculation of EigenValues and EigenVectors using same algorithm as Matlab function:

        [V,D] = eig(A,B) produces a diagonal matrix D of generalized
        eigenvalues and a full matrix V whose columns are the corresponding
        eigenvectors so that A*V = B*V*D.

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