Quantcast
Channel: Intel® Integrated Performance Primitives
Viewing all 1040 articles
Browse latest View live

Compare

$
0
0

Compares two strings of the fixed length.

Syntax

IppStatus ippsCompare_8u(const Ipp8u*pSrc1, const Ipp8u*pSrc2, intlen, int*pResult);

Include Files

ippch.h

Domain Dependencies

Headers: ippcore.h, ippvm.h, ipps.h

Libraries: ippcore.lib, ippvm.lib, ipps.lib

Parameters

pSrc1

Pointer to the first source string.

pSrc2

Pointer to the second source string.

len

Maximum number of elements to be compared.

pResult

Pointer to the result.

Description

This function compares first len elements of two strings pSrc1 and pSrc2. The value pResult = pSrc1[i]- pSrc2[i] is computed successively for each i-th element, i =0,...len-1. When the first pair of non-matching elements occurs (that is, when pResult is not equal to zero), the function stops operation and returns the value pResult. The returned value is positive when pSrc1[i]> pSrc2[i] and negative when pSrc1[i]< pSrc2[i]. If the strings are equal, the function returns pResult = 0. The comparison is case-sensitive.

Return Values

ippStsNoErr

Indicates no error.

ippStsNullPtrErr

Indicates an error condition if at least one of the specified pointers is NULL.

ippStsLengthErr

Indicates an error condition if len is negative.

Example

The code example below shows how to use the function ippsCompare_8u.

 Ipp8u string0[] = "These functions compare two strings";
 Ipp8u string1[] = "These FUNCTIONS compare two strings";
 int result;
 ippsCompare_8u( string0, string1, sizeof (string0) - 1, &result );
 printf ( "ippsCompare_8u said: " );
 printf ( "string0 is %s string1.\n", (result < 0) ? "less than" :
 ((result > 0) ? "greater than" : "equal to") );
 ippsCompareIgnoreCaseLatin_8u( string0, string1, sizeof (string0) - 1,&result );
 printf ( "ippsCompareIgnoreCaseLatin_8u said: " );
 printf ( "string0 is %s string1.\n", (result < 0) ? "less than" :
 ((result > 0) ? "greater than" : "equal to") );

 Output:
 ippsCompare_8u said: string0 is greater than string1.
 ippsCompareIgnoreCaseLatin_8u said: string0 is equal to string1.

WTHaarFwd, WTHaarInv

$
0
0

Performs forward or inverse single-level discrete wavelet Haar transforms.

Syntax

Case 1: Forward transform

IppStatus ippsWTHaarFwd_32f(const Ipp32f*pSrc, intlen, Ipp32f*pDstLow, Ipp32f*pDstHigh);

IppStatus ippsWTHaarFwd_64f(const Ipp64f*pSrc, intlen, Ipp64f*pDstLow, Ipp64f*pDstHigh);

IppStatus ippsWTHaarFwd_16s_Sfs(const Ipp16s*pSrc, intlen, Ipp16s*pDstLow, Ipp16s*pDstHigh, intscaleFactor);

Case 2: Inverse transform

IppStatus ippsWTHaarInv_32f(const Ipp32f*pSrcLow, const Ipp32f*pSrcHigh, Ipp32f*pDst, intlen);

IppStatus ippsWTHaarInv_64f(const Ipp64f*pSrcLow, const Ipp64f*pSrcHigh, Ipp64f*pDst, intlen);

IppStatus ippsWTHaarInv_16s_Sfs(const Ipp16s*pSrcLow, const Ipp16s*pSrcHigh, Ipp16s*pDst, intlen, intscaleFactor);

Include Files

ipps.h

Domain Dependencies

Headers: ippcore.h, ippvm.h

Libraries: ippcore.lib, ippvm.lib

Parameters

pSrc

Pointer to the source vector for forward transform.

len

Number of elements in the vector.

pDstLow

Pointer to the array with the coarse “low frequency” components of the output for forward transform.

pDstHigh

Pointer to the array with the detail “high frequency” components of the output for forward transform.

pSrcLow

Pointer to the array with the coarse “low frequency” components of the input for inverse transform.

pSrcHigh

Pointer to the array with the detail “high frequency” components of the input for inverse transform.

pDst

Pointer to the array with the output signal for inverse transform.

scaleFactor

Scale factor, refer to Integer Scaling.

Description

These functions perform forward and inverse single-level discrete Haar transforms. These transforms are orthogonal and reconstruct the original signal perfectly.

The forward transform can be considered as wavelet signal decomposition with lowpass decimation filter coefficients {1/2, 1/2} and highpass decimation filter coefficients {1/2, -1/2}.

The inverse transform is represented as a wavelet signal reconstruction with lowpass interpolation filter coefficients {1, 1} and highpass interpolation filter coefficients {-1, 1}.

The decomposition filter coefficients are frequency response normalized to provide the same value range for both input and output signals. Thus, the amplitude of the low pass filter frequency response is 1 for zero-valued frequency, and the amplitude of the high pass filter frequency response is also 1 for the frequency value near to 0.5.

As the absolute values of the interpolation filter coefficients are equal to 1, the reconstruction of the signal requires few operations. It is well suited for usage in data compression applications. As the decomposition filter coefficients are powers of 2, the integer functions perform lossless decomposition with the scaleFactor value equal to -1. To avoid saturation, use higher-precision data types.

Note that the filter coefficients can be power spectral response normalized, see [Strang96] for more information. Thus, the decomposition filter coefficients are {2-1/2, 2-1/2} and {2-1/2, -2-1/2}; accordingly; the reconstruction filter coefficients are {2-1/2, 2-1/2} and {-2-1/2, 2-1/2}.

In the following definition of the forward single-level discrete Haar transform, N = len. The coarse “low-frequency” component c(k) is pDstLow[k] and the detail “high-frequency” component d(k) is pDstHigh[k]; also x(2k) and x(2k+1) are even and odd values of the input signal pSrc, respectively.

c(k) = (x (2k) + x(2k+1 ))/2

d(k) = (x(2k+1) - x(2k))/2

In the inverse direction, N= len. The coarse “low-frequency” component c(k) is pSrcLow[k] and the detail “high-frequency” component d(k) is pSrcHigh[k]; also y(2i) and y(2i+1) are even and odd values of the output signal pDst, respectively.

y(2i) = c(i) - d(i)

y(2i+1) = c(i) + d(i)

For even length N, 0 ≤ k< N/2 and 0 ≤ i< N/2. Also, “low-frequency” and “high-frequency” components are of size N/2 for both original and reconstructed signals. The total length of components is equal to the signal length N.

In case of odd length N, the vector is considered as a vector of the extended length N+1 whose two last elements are equal to each other x[N] = x[N - 1]. The last elements of the coarse and detail components of the decomposed signal are defined as follows:

c((N+1 )/2 - 1) = x(N - 1)

d((N + 1)/2 - 1) = 0

Correspondingly, the last element of the reconstructed signal is defined as:

y(N) = y(N - 1) = c((N+ 1)/2 - 1)

For odd length N, 0 ≤ k< N - 1)/2 and 0 ≤ i< N - 1)/2 , assuming that c((N+ 1)/2 - 1) = x(N - 1) and y(N - 1) = c((N + 1)/2 - 1). The “low-frequency” component is of size (N + 1)/2. The “high-frequency” component is of size (N - 1)/2, because the last element d((N + 1)/2 - 1) is always equal to 0. The total length of components is also N.

Such an approach applies continuation of boundaries for filters having the symmetry properties, see [Bris94].

When performing block mode transforms, take into consideration that for decomposition and reconstruction of even-length signals no extrapolations at the boundaries is used. In case of odd-length signals, a symmetric continuation of the signal boundary with the last point replica is applied.

When it is necessary to have a continuous set of output blocks, all the input blocks are to be of even length, besides the last one (which can be either of odd or even length). Thus, if the whole amount of elements is odd, only the last block can be of odd length.

ippsWTHaarFwd. Thise function performs the forward single-level discrete Haar transform of a len-length signal pSrc and stores the decomposed coarse “low-frequency” components in pDstLow, and the detail “high-frequency” components in pDstHigh.

ippsWTHaarInv. This function performs the inverse single-level discrete Haar transform of the coarse “low-frequency” components pSrcLow and detail “high-frequency” components pSrcHigh, and stores the reconstructed signal in the len-length vector pDst.

For more information on wavelet transforms see [Strang96] and [Bris94].

Return Values

ippStsNoErr

Indicates no error.

ippStsNullPtrErr

Indicates an error when the pDst or pSrc pointer is NULL.

ippStsSizeErr

Indicates an error when len is less than 4 for the function ippsWinBlackmanOpt and less than 3 for all other functions of the family.

Example

The example below illustrates the use of the function ippsWTHaarFwd_32f.

IppStatus wthaar(void)
 {     Ipp32f x[8], lo[4], hi[4];
       IppStatus status;
       ippsSet_32f(7, x, 8);
                                        --x[4];
       status = ippsWTHaarFwd_32f(x, 8, lo, hi);
       printf_32f(“WT Haar low  =”, lo, 4, status);
       printf_32f(“WT Haar high =”, hi, 4, status);
       return status;  }

Output:

WT Haar low  =  7.000000 7.000000 6.500000 7.000000
     WT Haar high =  0.000000 0.000000 0.500000 0.000000

Project migration from IPP 8.x to IPP 9.0 -- need help on replacing removed functionality

$
0
0

Starting with IPP 9.0, Intel has completely removed all JPEG-related functions including Huffman and color space conversions. Color space conversions I can handle on my own, but I am not in the mood to implement multi-threaded JPEG and Huffman parts from scratch. I had a working solution with UIC and IPP 8.x, now I have a broken build.

Sure, I can choose between staying on 8.x and miss on all performance improvements for new CPUs and all bugfixes / new features and upgrading to 9.0 while losing the most important part of my image viewer application -- (fast) JPEG decoding.

I would really appreciate some guidance from the Intel IPP product manager who decided to axe IPPJ domain on how to replace the missing functionality which was provided with it in previous IPP versions, preferrably in the shortest possible time span with minimal effort.

My requirements are quite simple -- multi-threaded JPEG decoding from memory stream. How to accomplish this using IPP 9.0?

AESSetKey

$
0
0

Resets the AES secret key in the initialized IppsAESSpec context.

Syntax

IppStatus ippsAESSetKey(const Ipp8u*pKey, intkeylen, IppsAESSpec*pCtx);

Include Files

ippcp.h

Domain Dependencies

Headers: ippcore.h

Libraries: ippcore.lib

Parameters

pKey

Pointer to the AES key.

keylen

Length of the secret key.

pCtx

Pointer to the initialized IppsAESSpec context.

Description

This function resets the AES secret key in the initialized IppsAESSpec context with the user-supplied secret key.

Note

If the pKey pointer is NULL, the function resets the context with the zero key, which can help you to clean up the actual secret before releasing the context.

Return Values

ippStsNoErr

Indicates no error. Any other value indicates an error or warning.

ippStsNullPtrErr

Indicates an error condition if the pCtx pointer is NULL.

ippStsLengthErr

Returns an error condition if keyLen is not equal to 16, 24, or 32.

is std:sort faster than ipp sort ippsSortDescend_64f_I

$
0
0

hi,

I am trying to benchmark std::sort on vectors of double vs ipp sort using (ippsSortDescend_64f_I). I am sorting 200 vectors of length 2000 elements each.  My test program is attached in this post. I see that std::sort is consistently performing better ( at least 10 times faster) than ipp sort. Is this expected behavior? I would prefer to move to ipp assuming its better in performance but i am not able to prove it. What am I doing wrong in my test program? 

#include <array>
#include <iostream>
#include <algorithm>
#include <stdlib.h>
#include <time.h>
#include <sys/time.h>
#include <sys/timeb.h>

#include <vector>
#include <chrono>

#include "ipp.h"

using namespace std;

const int SIZE = 2000000;
const int ITERS = 200;

//Chrono typedefs
typedef std::chrono::high_resolution_clock Clock;
typedef std::chrono::microseconds microseconds;

//////////////////////////////////// std ///////////////////////////////////

typedef vector<double> myList;

void initialize(myList & l, Ipp64f* ptr)
{
    double randomNum;
    for (int i = 0; i < SIZE; i++)
    {
        randomNum =  1.0 * rand() / (RAND_MAX / 2) - 1;
        l.push_back(randomNum);
        				ptr[i] = randomNum;
    }
}

void test_sort()
{
    		array<myList, ITERS> list;
    		array<Ipp64f*, ITERS> ippList;

    		// allocate
    for(int i=0; i<ITERS;i++)
    {
      				list[i].reserve(SIZE);
      				ippList[i] = ippsMalloc_64f(SIZE);
    		}

    		// initialize
    		for(int i=0;i<ITERS;i++)
    		{
        				initialize(list[i], ippList[i]);
    		}

    		cout << "\n\nTest Case 1: std::sort\n";
    cout << "========================\n";

    		// sort vector
    		Clock::time_point t0 = Clock::now();
    for(int i=0; i<ITERS;i++)
    {
        std::sort(list[i].begin(), list[i].end());
    }
    		Clock::time_point t1 = Clock::now();
    		microseconds ms = std::chrono::duration_cast<microseconds>(t1 - t0);
    		std::cout << ms.count() << " micros"<< std::endl;

    		////////////////////////////////// IPP ////////////////////////////////////////

   		 cout << "\n\nTest Case 2: ipp::sort\n";
    cout << "========================\n";

    		// sort ipp
    		Clock::time_point t2 = Clock::now();
    		for(int i=0; i<ITERS;i++)
    {
      				ippsSortAscend_64f_I(ippList[i], SIZE);
    }
    		Clock::time_point t3 = Clock::now();
    		microseconds ms1 = std::chrono::duration_cast<microseconds>(t3 - t2);
    		std::cout << ms1.count() << " micros"<< std::endl;

    		for(int i=0; i<ITERS;i++)
    		{
	        ippsFree( ippList[i] );
    		}
}


///////////////////////////////////////////////////////////////////////////////////////

int main()
{
    srand (time(NULL));

    cout << "Test for sorting an array of structures.\n"<< endl;
    cout << "Test case: \nSort an array of structs ("<<ITERS<<" iterations) with double of length "<<SIZE<<". \n";
    		IppStatus status=ippInit();
    		test_sort();
    return 0;
}

///////////////////////////////////////////////////////////////////////////////////////
 

Getting Help and Support

$
0
0

Getting Help

You can get context-sensitive help for the Intel® Integrated Performance Primitives (Intel® IPP) in the Microsoft Visual Studio* development system on Windows* OS. To do this, select the function name in the code editor, and click F1.

Getting Technical Support

If you did not register your Intel software product during installation, please do so now at the Intel® Software Development Products Registration Center. Registration entitles you to free technical support, product updates and upgrades for the duration of the support term.

For general information about Intel technical support, product updates, user forums, FAQs, tips and tricks and other support questions, please visit http://www.intel.com/software/products/support/.

Note

If your distributor provides technical support for this product, please contact them rather than Intel.

For technical information about the Intel IPP library, including FAQ's, tips and tricks, and other support information, please visit the Intel IPP forum: http://software.intel.com/en-us/forums/intel-integrated-performance-primitives/ and browse the Intel IPP knowledge base: http://software.intel.com/en-us/articles/intel-ipp-kb/all/.

Tme to say good bye....

$
0
0

With release 9.0 you shot up anything.

"The following Intel® IPP domains are legacy, and they are removed from the main packages: Audio Coding (ippAC), Video Coding (ippVC), Speech Coding (ippSC), Image Compression (ippJP), Data Integrity (ippDI), Generated Transforms (ippGEN), Small Matrices (ippMX), and Realistic Rendering (ippRR). That means these domains won't be optimized for new architectures (the latest optimizations are targeted for Intel® Advanced Vector Extensions 2) and any newly detected performance and stability issues won't be fixed. Find the alternative suggestion for the deprecated functions."

 

Because your alternatives are only media sdk and it's closed source intel has lost a customer.

I will use now ffmepg.

Regards

 

 

 

ippiConvFull_32f_C1R error in IPP7.0

$
0
0

Hi, I test ippiConvFull_32f_C1R under VS2010 and IPP 7.0 on my computer. The cpu

is i5-3470 CPU@3.20GHz. 

I find when the kernel size is larger than 10*10, then the result is not correct. the code as follows:

    int   nWidth = 81;
    int   nHeight = 80;
    float *pfsrc = new float[nWidth*nHeight];

    for(int i = 0; i < nWidth*nHeight; i++)
        pfsrc[i] = i;

    int nKWidth = 11;
    int nKHeight = 11;
    float psKernel[200];

    for(int i = 0; i < nKWidth*nKHeight;i++)
    {
        psKernel[i] = i%20;
    }

    int nDstW = nWidth + nKWidth - 1;
    int nDstH = nHeight + nKHeight - 1;

    float *psDst = new float[(nDstW)*(nDstH)];
    float *psDst2 = new float[(nDstW)*(nDstH)];

    IppiSize srcSize = {nWidth, nHeight};
    IppiSize kernelSize = {nKWidth, nKHeight};
    ippiConvFull_32f_C1R(pfsrc, nWidth*4, srcSize, psKernel, nKWidth*4, kernelSize, psDst, nDstW*4);

Does the code or ippiConvFull_32f_C1R have problem? By the way, I find some information text in include file about this function.

//  Purpose: Performs the VALID 2-D convolution of matrices (images).
//           If IppiSize's of matrices (images) are Wa*Ha and Wb*Hb
//           correspondingly, then the IppiSize of the resulting matrix
//           (image) will be (|Wa-Wb|+1)*(|Ha-Hb|+1).
//           If the smallest image IppiSize > CRITERION, then convolution
//           is done using 2D FFT.

Maybe the problem is related to 2D FFT? 

Thank you!

 


convert function UYVY to YUY2

$
0
0

Hello There!

I'm searching for hours now and i still can't find a function to convert UYVY(4:2:2) to YUY2 (4:2:2) image.

Please help!

kind regards,

Max

 

Old new license

$
0
0

Hi all,

My question is quite unusual,

2 years ago I asked our management for IPP license specially for my PC, but I received negative answer.
Yesterday I received a message from our IT department that IPP license for me has been bought...   But it appeared that they did it one year ago (08.2014) and forgot about it successfully.
As a result we have Intel license (*.lic file) for Intel Parallel Studio XE Composer Edition for Windows from 08.2014.
I'd like to enable this license.

My questions are:

1. Is it necessary to install Intel Parallel Studio XE from 08.2014 or I can install any version that provided by Intel web-site?
2. If Intel will produce the next version of IPP (may be IPP 10.0), will it be possible to update IPP with our license or it will require a purchase of a new license?

Best regards,

Roman

ippiLabelMarker Issues

$
0
0

Hi All,

I am trying to do some image segmentation, and I am still having some trouble with ippiLabelMarker's implementation even after reading through the documentation and this post: https://software.intel.com/en-us/forums/topic/297054

Here is a snippet of my code:

//get size and allocate memory for buffer
	int LabelBufferSize;
	ippiLabelMarkersGetBufferSize_8u_C1R(sizeImg, &LabelBufferSize);
	Ipp8u* LabelBuffer = ippsMalloc_8u(LabelBufferSize);

//Compute Labels
	int minLabel = 0;
	int maxLabel = 255;
	int numLabels;
	ippiLabelMarkers_16u_C1IR(BinUnsigned, src16Step, sizeImg, minLabel, maxLabel, ippiNormL1, &numLabels, LabelBuffer);
	std::cout << numLabels << std::endl;

My first argument of the LabelMarkers function is "BinUnsigned", an Ippi16u* binarized image with pixel values of 0 and 254. 

Based on the forum post linked above and all the documentation I've read, my understanding is that the LabelMarker image should apply a different label to each continuous section of non-zero values. Is this correct?

I'm seeing the same label applied to sections that are clearly separated by zeros, seemingly just because they have the same value (which will always be 254).

Also, numLabels in the above instance returns 3, even though I verified that there are no other label values in the LabelMarker other than 0 and 254. Can anyone explain to me what's going on there?

Any help would be greatly appreciated, thanks!

platform toolset V120_xp with IPP

$
0
0

Hi all !

I'm working with visual studio 2013.

My project need to be WINDOWS XP compliant, thus I need to set the visual studio project option "Platform Toolset" to the value "V120_xp".

But, If i use the "V120_xp", the "Intel performance libraries" option disappears and I can't choose to use IPP libraries in my Visual Studio project.

I would like to know if the IPP option is not present because of some known issues between IPP and V120_xp or it is only a bug of the IPP Visual Studio integration.

Thanks

Matteo

ippsDecodeAdaptiveVector

$
0
0

Hi,

I am using IPP G729 functions in my application The application is developed on Win 7 64 bit platform. 

We have observed different results when running the  ippsDecodeAdaptiveVector function between the 32-bit and the 64-bit version of the IPP libraries.
Specifically we are calling:  ippsDecodeAdaptiveVector_G729_32f_I.     

We are currently running IPP 8.2 Update 1, for Linux.

The binary results differ between the 32 and 64 bit libraries.  Is this expected? 

Thanks

Need ippSC functions removed in 9.0

$
0
0

I just upgraded my Parallel Studio XE to 2016 and there was no longer an option for including the ippSC functions.

Can I get the missing ippSC functions for 9.0 or can I downgrade just IPP back to 8.2?

I can't find a download link for IPP 8.2 with update 2 anymore.  Is there a way I can download the latest IPP that still had ippSC?

Cryptography 8.2

$
0
0

I have the main IPP installation package (Windows):

w_ipp_8.2.2.208 (and .148)

The latest cryptography package is

w_ccompxe_crypto_ipp_8.2.2.221_intel64

This package will not install, because it requests to install IPP 8.2.2.221 first ... but I cannot find that anywhere

 

Please help


Intel® System Studio Release Notes and Getting Started Documents

$
0
0

This page provides the current Release Notes and Getting Started Documents for Intel® System Studio 2016.

To get product updates, log in to the Intel® Software Development Products Registration Center.

For questions or technical support, visit Intel® Software Products Support.

Contents

 

Current Release Notes

Intel® System Studio 2016 for Linux* and Android*(1)

(1) Android*, Linux*, Embedded Linux*, Yocto Project*, Wind River* Linux*

Studio ComponentLinux* Host Windows* Host

What's New

What's new?

What's new?

Intel® System Studio (full product)

Version 2016

Version 2016

Intel® C++ Compiler

Version 16.0

Version 16.0

Intel® Math Kernel Library

Version 11.3

Version 11.3

Intel® Integrated Performance Primitives

Version 9.0

Version 9.0

Intel® Threading Building Blocks

Version 4.4

Version 4.4

Intel® VTune™ Amplifier for Systems

Version 2016

Version 2016

Intel® Energy Profiler

Version 2016

Version 2016

Intel® Inspector for Systems

Version 2016

Version 2016

Intel® System Studio System Analyzer,Frame Analyzer and Platform Analyzer

Version 2015 R1

Version 2015 R1

Intel® System Debugger

Version 2016

Version 2016

GDB - The GNU* Project Debugger

Version 7.8.1

Version 7.8.1

Intel® System Studio 2016 for Windows*

Studio ComponentWindows* Host

What's New

What's new?

Intel® System Studio for Windows* (full product)

Version 2016

Intel® C++ Compiler

Version 16.0

Intel® Math Kernel Library

Version 11.3

Intel® Integrated Performance Primitives

Version 9.0

Intel® Threading Building Blocks

Version 4.4

Intel® VTune™ Amplifier for Systems

Version 2016

Intel® Energy Profiler

Version 2016

Intel® Inspector for Systems

Version 2016

Intel® System Studio System Analyzer, Frame Analyzer and Platform Analyzer for Windows*

Version 2015 R1

Intel® System DebuggerVersion 2016

Older Release Notes

Intel® System Studio

Linux* Host Windows* Host
 Version 2015 Update 3Version 2015 Update 3
 

Version 2015 Update 2

Version 2015 Update 2

 

Version 2015 Update 1

Version 2015 Update 1

 

Version 2015

Version 2015

 

Version 2014 Update 2

Version 2014 Update 2

 

Version 2014 Update 1

Version 2014 Update 1

 

Version 2014

Version 2014

 

Version 2013 Update 2

 

 

Version 2013 Update 1

 

 

Version 2013

 

 

Intel® System Studio 2015

Getting Started Guide

Studio Componentfor Linux* and Android*
(Linux* Host)
for Linux* and Android*
(Windows* Host)
for Windows*

Intel® System Studio

Getting Started Guide

Getting Started Guide

Getting Started Guide

Intel® C++ Compiler for Linux* and Android* targets

Intel® C++ Compiler Getting Started Guide

Intel® C++ Compiler Getting Started Guide

 

Intel® Integrated Performance Primitives

Getting Started with Intel® Integrated Performance Primitives
Building Android* NDK Applications with Intel® IPP

Getting Started with Intel® Integrated Performance Primitives

Getting Started with Intel® Integrated Performance Primitives

Intel® Math Kernel Library

Using Intel® Math Kernel Library

Using Intel® Math Kernel Library

Using Intel® Math Kernel Library

Intel® VTune™ Amplifier for Systems

Getting Started Guide

Getting Started Guide

Getting Started Guide

Intel® Inspector for Systems

Intel® Inspector for Systems Getting Started Guide

Intel® Inspector for Systems Getting Started Guide

Intel® Inspector for Systems Getting Started Guide

Intel® System Studio System Analyzer

Intel® System Studio System Analyzer Getting Started Guide

Intel® System Studio System Analyzer Getting Started Guide

Intel® System Studio System Analyzer Getting Started Guide

Intel® System Debugger

Intel® System Debugger Quickstart Guide

Intel® System Debugger Quickstart Guide

 

Intel-enhanced GNU* GDB

GNU* GDB Getting Started Guide
GNU* GDB Quickstart Guide

GNU* GDB Getting Started Guide
GNU* GDB Quickstart Guide

 

 

Intel® System Studio 2015

User Guide

Studio ComponentLinux* HostWindows* Host

Intel® System Studio

User Guide

User Guide

Intel® Math Kernel Library

User's Guide for Intel® Math Kernel Library

User's Guide for Intel® Math Kernel Library (Linux* Target)
User's Guide for Intel® Math Kernel Library (Windows* Target)

Intel® VTune™ Amplifier for Systems

Sampling Enabling Product User's Guide

Sampling Enabling Product User's Guide

Intel® Energy Profiler

SoC Watch Tool User's Guide

SoC Watch Tool User's Guide

 

WakeUp Watch Tool for Android* User's Guide

WakeUp Watch Tool for Android* User's Guide

Graphics Performance Analysis Tools

Intel® System Studio System Analyzer

Intel® System Studio System Analyzer, Frame Analyzer and Platform Analyzer

Intel® System Debugger

Use Cases for the Intel® System Debugger

Use Cases for the Intel® System Debugger

 

Intel® System Debugger User's Guide

Intel® System Debugger User's Guide

SVEN SDK

SVEN SDK User Guide

SVEN SDK User Guide

 

SVEN Trace Viewer User Guide

SVEN Trace Viewer User Guide

GDB - The GNU* Project Debugger

Debugging with GDB

Debugging with GDB

  • Developers
  • Intel AppUp® Developers
  • Android*
  • Linux*
  • Tizen*
  • Yocto Project
  • C/C++
  • Beginner
  • Intermediate
  • Intel® System Studio
  • Intel® Math Kernel Library
  • Intel® Integrated Performance Primitives
  • Debugging
  • Development Tools
  • Embedded
  • URL
  • Learning Lab
  • Last Updated: 

    Monday, October 27, 2014

    DilateBorder: Doc error?

    $
    0
    0

    The documentation for DilateBorder has a code example of a dilation of a 5x5 image, defined as

        Ipp16u pSrc[5*5] = { 1, 2, 4, 1, 2,
                            5, 1, 2, 1, 2,
                            1, 2, 1, 2, 1,
                            2, 1, 5, 1, 2};

    Isn't a line missing in there?

    IPP version is 9.0.0.

    Is the Intel® IPP Asynchronous C/C++ library included in the standard IPP library?

    $
    0
    0

    I have searched the site quite rigorously but have been unable to determine for sure if the asynchronous library described here (http://registrationcenter.intel.com/irc_nas/3727/ipp_async_get_started.htm) is available as part of the library downloaded from here (https://software.intel.com/en-us/intel-ipp).

    Note: I have actually installed Student version of Intel Parallel Studio XE Cluster Edition for windows (https://software.intel.com/en-us/qualify-for-free-software/student), which as far as I can tell includes the ipp library linked above.

    I intend to use the library as part of OpenCV-3.0, which I have successfully built without ipp_a for the time being using cmake (http://docs.opencv.org/3.0-beta/doc/tutorials/introduction/windows_install/windows_install.html).

    My end goal for now is to be able to run this tutorial successfully (http://docs.opencv.org/3.0-beta/doc/tutorials/core/how_to_use_ippa_conversion/how_to_use_ippa_conversion.html#howtouseippaconversion)

    Any feedback appreciated! Thanks

    Codec support

    $
    0
    0

    Does Intel plan to support the newer EVS codec for LTE usage within IPP. I think it might replace AMR_WB

    ippiResizeSqrPixel_xxx in IPP 9.0 ?

    $
    0
    0

    From the compilation errors I get when tyring to port a project to Parallel Studio 2016 (installation package = parallel_studio_xe_2016_setup.exe)

    It looks like these (very useful) functions are all gone in IPP 9.0 :

    ippiResizeGetBufSize
    ippiResizeSqrPixel_8u_C3R
    ippiResizeSqrPixel_8u_C1R
    ippiResizeSqrPixel_32f_C1R

    I'll be glad to learn which new/renamed functions one is supposed to use as replacement.

    I'm back to Parallel Studio 2015 and IPP 8.0 at the moment.

     

    Viewing all 1040 articles
    Browse latest View live


    <script src="https://jsc.adskeeper.com/r/s/rssing.com.1596347.js" async> </script>