openmp

问题 I am new to OpenMP and I just tried to write a small program with the parallel for construct. I have trouble understanding the output of my program. I don't understand why thread number 3 prints the output before 1 and 2. Could someone offer me an explanation? So, the program is: #pragma omp parallel for for (i = 0; i < 7; i++) { printf("We are in thread number %d and are printing %d\n", omp_get_thread_num(), i); } and the output is: We are in thread number 0 and are printing 0 We are in

问题 I am trying to implement a argmax with OpenMP. If short, I have a function that computes a floating point value: double toOptimize(int val); I can get the integer maximizing the value with: double best = 0; #pragma omp parallel for reduction(max: best) for(int i = 2 ; i < MAX ; ++i) { double v = toOptimize(i); if(v > best) best = v; } Now, how can I get the value i corresponding to the maximum? Edit: I am trying this, but would like to make sure it is valid: double best_value = 0; int best

问题 Without using Open MP Directives - serial execution - check screenshot here Using OpenMp Directives - parallel execution - check screenshot here #include "stdafx.h" #include <omp.h> #include <iostream> #include <time.h> using namespace std; static long num_steps = 100000; double step; double pi; int main() { clock_t tStart = clock(); int i; double x, sum = 0.0; step = 1.0 / (double)num_steps; #pragma omp parallel for shared(sum) for (i = 0; i < num_steps; i++) { x = (i + 0.5)*step; #pragma

问题 I've been trying to increase the performance of my OpenMP solution which often has to deal with nested loops on arrays. Although I've managed to bring it down to 37 from 59 seconds of the serial implementation (on an ageing dual-core Intel T6600) I'm worried that cache synch gets lots of CPU attention (when the CPU should be solving my problem!). I've been fighting to set up the profiler so I haven't verified that claim but my question stands regardless. According to this lecture on load

问题 I wonder if there is any technique to create parallel sections in OpenMp using a for-loop. For example, instead of creating n different #pragma omp sections, I want to create them using an n-iteration for-loop with some changing parameters for each section. #pragma omp parallel sections { #pragma omp section { /* Executes in thread 1 */ } #pragma omp section { /* Executes in thread 2 */ } #pragma omp section { /* Executes in thread n */ } } 回答1: With explicit OpenMP tasks: #pragma omp

问题 The cluster that I work with recently switched from SGE to SLURM. I was wondering what the difference between sbatch options --ntasks and --cpus-per-task ? --ntasks seemed appropriate for some MPI jobs that I ran but did not seem appropriate for some OpenMP jobs that I ran. For the OpenMP jobs in my SLURM script, I specified: #SBATCH --ntasks=20 All the nodes in the partition are 20core machines, so only 1 job should run per machine. However, multiple jobs were running simultaneously on each

问题 I assume thread creation and deletion could be costly. Does OpenMP try reuse existing threads? For example, #pragma omp parallel sections num_threads(4) { #pragma omp section { ... worker A ... } #pragma omp section { ... worker B ... } } #pragma omp parallel sections num_threads(4) { #pragma omp section { ... worker C ... } #pragma omp section { ... worker D ... } } In execution, does OpenMP allocate 5 threads or 3 (in which C and D reuse the threads that A and B used)? 回答1: In your example,

问题 In my C++ program, I'd like to run its executable sometimes with and sometimes without using OpenMP (i.e. multi-threading or single-threading). I am considering any of the following two cases how my code is using OpenMP: (1) Assume that my code is only having #include <omp.h> and OpenMP directives. (2) Same as (1) and my code further calls OpenMP functions like omp_get_thread_num() . In order not to have different code for different running, is it the only way using some self-defined

问题 I'm sitting with some stuff here trying to make orphaning work, and reduce the overhead by reducing the calls of #pragma omp parallel . What I'm trying is something like: #pragma omp parallel default(none) shared(mat,mat2,f,max_iter,tol,N,conv) private(diff,k) { #pragma omp master // I'm not against using #pragma omp single or whatever will work { while(diff>tol) { do_work(mat,mat2,f,N); swap(mat,mat2); if( !(k%100) ) // Only test stop criteria every 100 iteration diff = conv[k] = do_more

问题 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