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Simple OpenMP
Mike Bailey
openmp-simple.pptx

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mjb – March 16, 2020
OpenMP Multithreaded Programming
OpenMP stands for “Open Multi-Processing”
It is run by a consortium of companies, labs, and universities
OpenMP (IMHO) gives you the biggest multithread benefit per amount of work you have to put into using it
mjb – March 16, 2020
Computer Graphics
Much of your use of OpenMP will be accomplished by issuing C/C++ “pragmas” to tell the compiler how to build the threads into the executable
#pragma omp directive [clause]
That’s it! That’s where the compiler comes in.
But, as you are about to find out, doing parallel processing at
all is not difficult.
The trick is doing parallel processing well.
That’s where you come in.
Computer Graphics
mjb – March 16, 2020
Using OpenMP in Linux:
g++ -o proj proj.cpp -lm -fopenmp
Using OpenMP in Microsoft Visual Studio:
1. Go to the Project menu → Project Properties
2. Change the setting Configuration Properties → C/C++ → Language →
OpenMP Support to “Yes (/openmp)”
Computer Graphics
mjb – March 16, 2020
Threads are at their very best when each one can run on a separate hardware core.
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We will get into more detail pretty soon, but for now, know that a thread is an independent execution path for your code to take.
mjb – March 16, 2020
Computer Graphics
Seeing if OpenMP is Supported on Your System:
#ifndef _OPENMP
fprintf( stderr, “OpenMP is not supported – sorry!\n” ); exit( 0 );
How to find out how many cores your system has:
int numprocs = omp_get_num_procs();
How to specify how many OpenMP threads you want to reserve starting now:
omp_set_num_threads( num );
How to use one thread per core:
omp_set_num_threads( omp_get_num_procs( ) );
mjb – March 16, 2020

Creating OpenMP threads for a for loop
#include
omp_set_num_threads( NUMT ); …
#pragma omp parallel for default(none)
The code starts out executing in a single thread
This sets how many threads will be in the thread pool. It doesn’t create them yet, it just says how many will be used the next time you ask for them.
This creates a team of threads from the thread pool and divides the for-loop passes up among those threads
for( int i = 0; i < arraySize; i++ ) { This tells the compiler to parallelize the for-loop into multiple threads. Each thread automatically gets its own personal copy of the variable i because it is defined within the for- loop body. There is an “implied barrier” at the end where each thread waits until all threads are done, then the code continues in a single thread Computer Graphics mjb – March 16, 2020 The default(none) directive forces you to explicitly declare all variables declared outside the parallel region to be either private or shared while they are in the parallel region. Variables declared within the for-loop statement are automatically private 程序代写 CS代考 加微信: powcoder QQ: 1823890830 Email: powcoder@163.com