openmp

I'm using Intel IPP for multiplication of 2 Images (Arrays). I'm using Intel IPP 8.2 which comes with Intel Composer 2015 Update 6. I created a simple function to multiply too large images (The whole project is attached, see below). I wanted to see the gains using Intel IPP Multi Threaded Library. Here is the simple project (I also attached the complete project form Visual Studio): #include "ippi.h" #include "ippcore.h" #include "ipps.h" #include "ippcv.h" #include "ippcc.h" #include "ippvm.h" #include <ctime> #include <iostream> using namespace std; const int height = 6000; const int width =

I have the following class: Class L{ public: bool foo(vector<bool> & data); private: C** cArray; } and would like to parallelize the for loop in the function foo which is called somtime after an object of L is created and all the elements in cArray are initialized. bool L::foo(vector<int> & data){ int row, col; #pragma omp parallel shared(SIZE, cArray, data) private(row, col) for (row=0, row<SIZE; ++row) { for (col=0; col<SIZE; ++col) { cArray[row][col].computeScore(data); } } } But this gives an error: error C3028: 'L::cArray' : only a variable or static data member can be used in a data

I am designing a C++ data structure (for graphs) which is to be used by parallel code (using OpenMP). Suppose I want to have a method which enables iteration over all elements (nodes). Of course, this iteration is going to be parallelized. Is it possible to use an iterator for this purpose? How should an iterator look like that enables parallel access? Would you advise for or against using iterators in this case? OpenMP parallel loops don't play nicely with iterators. You'll want to implement an indexing mechanism ( operator[] taking an integral argument) on your graph class. If you do want to

I have the following code, which I believe should display a progress bar approximating the progress of the entire process (since each parallel thread of the loop should be progressing at approximately the same rate) #pragma omp parallel for for(long int x=0;x<elevations.size1();x++){ #pragma omp master { progress_bar(x*omp_get_num_threads()); //Todo: Should I check to see if ftell fails here? } ........ } However, I get the following error: warning: master region may not be closely nested inside of work-sharing or explicit task region [enabled by default] Now, when I run the code I do get the

I am using OpenMP to do multithreading with my nested loops. Since new to this stuff, I am not sure if I am using OpenMP in the correct way so that it can actually do the parallel programming. So I like to know if I can measure the performance of my C++ program that uses OpenMP so I can tell it actually works and I am on the right track? Like how many threads are running in parallel and how long it takes for each of them to finish. Thanks and regards! #include <omp.h> ... int target_thread_num = 4; omp_set_num_threads(target_thread_num); unsigned long times[target_thread_num]; // Initialize

In Is OpenMP (parallel for) in g++ 4.7 not very efficient? 2.5x at 5x CPU , I determined that the performance of my programme varies between 11s and 13s (mostly always above 12s, and sometimes as slow as 13.4s) at around 500% CPU when using the default #pragma omp parallel for , and the OpenMP speed up is only 2.5x at 5x CPU w/ g++-4.7 -O3 -fopenmp , on a 4-core 8-thread Xeon. I tried using schedule(static) num_threads(4) , and noticed that my programme always completes in 11.5s to 11.7s (always below 12s) at about 320% CPU, e.g., runs more consistently, and uses less resources (even if the

We are using Xcode 4.5 on a C++11 project where we use OpenMP to speed up our computation: #pragma omp parallel for for (uint x=1; x<grid.width()-1; ++x) { for (uint y=1; y<grid.height()-1; ++y) { // code } } Although the Activity Monitor shows multiple threads being used by the program we observed that only one core is used: We also run the same code on Ubuntu using GCC 4.7 and we observed contention on all cores. Could it be that the OpenMP support has been removed in the Apple LLVM? Is there an alternative to OpenMP? We can't switch to GCC since we use C++11 features. Clang does not yet

The OpenMP used by the Intel compiler supports an environment variable KMP_BLOCKTIME ( docs ) which I believe controls the busy-waiting (spinlocked) time the threads will spend waiting for new work (linked document claims this defaults to 200ms). The OpenMP used by the Gnu compiler supports an environment variable GOMP_SPINCOUNT ( docs ) which I believe also controls that library's equivalent implementation detail (although apparently expressed as an iteration count rather than a time). My question is: what control(s) (if any) do Microsoft provide to control this parameter in the OpenMP used