Computação paralela

Difficulty understanding FFT documentation

I'm having a hard time understanding the docs for implementing an FFT , and some other minor issues.

1) when I look at the intel folder in my build environment, I see several dynamic libraries. Which one is necessary to implement the FFT

2) Also not clear if I should be using mkl instead of ipp for FFT

3) In trying to follow the example for using the FFT here : https://software.intel.com/en-us/articles/how-to-use-intel-ipp-s-1d-four...

Is it save to call ?feast_syev/?feast_heev from multiple threads?

Hi,

I'm developing an application that needs to compute various eigenvalue decompositions. Is it possible to call zfeast_heev from multiple threads in parallel? Ofcourse, each thread has it's own memory. I could not find this kind of information in the documentation. Currently I'm using zhpevd, which works fine when called from multiple threads, zfeast_heev however, do not.

Looking forward to your answers

 

Running OpenCV Computer Vision Programs on Xeon Phi

 

Hello,
I would like to know how to run opencv programs by using the intel xeon phi coprocessor card? What are my options? Also, how can i work with the Transparent API released by OpenCV and Xeon Phi ? Has Intel developed any module or support for running computer visions programs on the xeon phi?  Any suggestions or thoughts in this regard will be greatly appreciated.
Thankyou.

ippi function is undefined

I am trying to use the function ippiFilterBoxBorder and i keep getting a compiler error of
Error    4    error : identifier "y8_ippiFilterBoxBorder_16u_C1R" is undefined   
Error    3    error : identifier "y8_ippiFilterBoxBorderGetBufferSize" is undefined

If i change the FilterBoxBorder function to FilterBox (which is deprecated) everything compiles and runs with no issue.
I am using the latest c++ Intel compiler 15.0.2.179 on windows

Any idea what am i doing wrong?
 

 

Optimization problems with std::array maybe due to RVO

Hi,

I discovered a source of slowdown in my program, due to the usage of std::array. To gain a better understanding of what was going on, I have used my own implementation of std::array, and the slowdown disappeared. Unfortunately, I can't show you the program I am working on due to some non disclosure agreement. But I've managed to track down the problem and put it in a simple file.

When you compile the file shown below with

problem when multiple MPI versions installed

Dear all,

I have a problem to launch processes when multiple MPI versions installed. The processes work before I installed latest MPI 5.0.3.048:

C:\Program Files (x86)\Intel\MPI\4.1.3.047>mpiexec -wdir "Z:\test" -mapall -hosts 10 n01 6 n02 6 n03 6 n04 6 n05 6 n06 6 n07 6 n08 6 n09 6 n10 6 Z:\test

However, after I installed MPI 5.0.3.048, the following errors displayed when I launch mpiexec in the environment of 4.1.3.047:

Aborting: unable to connect to N01, smpd version mismatch

 

Trying to create an external bridge

Hi guys,

I'm trying to create an external bridge following the users guide from Intel.

First of all I execute the following command:

micctrl --addbridge=br0 --type=external --ip=<ip_HOST>

 

Then, I can see that a file ifcfg-br0 has created and I can see the bridge created with brctl show. Also I attached the eth1 interface to the bridge br0

 

Then, when I try execute:

 

micctrl --network=static --bridge=br0 --ip=<ip_MIC0>

 

I always obtain this error:

 

[Error] Bridge 'br0' not defined

Right Intel C++ compiler for 64-bit machine

Hello,

I just installed the Intel® Parallel Studio XE Professional Edition for C++ Linux* (evaluation version) for my Ubuntu 14.04.2 machine running on a "Intel Corporation Xeon E3-1200 Processor Family" processor.

I don't understand if this is a 32-bit compiler or not. I'm worried about this since during the installation a message reporting the absence of some 32-bit libraries appears on the console. 

Since I'm interested to have the best performances (running time) of my code, does a 64-bit specific version exist for my machine?

Thank you

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