Introduction to OpenMP

Introduction to OpenMP

OpenMP overview

Target hardware and software

• Target hardware is similar to thread programming
• Provide wrappers for threads and fork/join model of parallelism.
  • Program originally runs in sequential mode.
  • When parallelism is activated, multiple threads are forked from the original proces/thread (master thread).
  • Once the parallel tasks are done, threads are joined back to the original process and return to sequential execution.

• The threads have access to all data in the master thread. This is shared data.
• The threads also have their own private memory stack.

Basic requirements

• Source code (C) needs to include #include <omp.h>
• Compiling task need to have -fopenmp flag.
• Specify the environment variable OMP_NUM_THREADS.

Write, compile, and run an OpenMP program

OMP directives

• OpenMP must be told when to parallelize.
• For C/C++, pragma is used to annotate

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#pragma omp somedirective clause(value, othervalue)
  parallel statement;
 

• or

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#pragma omp somedirective clause(value, othervalue)
{
  parallel statement 1;
  parallel statement 2;
  ...
}
 

Hands-on: create hello_omp.c

• Log into molly
• Inside your csc466 directory, create a file called hello_omp.c with the following contents:

c linenums="1" --8<-- "docs/csc466/lectures/data/openmp/hello_openmp.c"

• Compile and run:

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gcc -o hello_omp hello_omp.c -fopenmp
export OMP_NUM_THREADS=4
./hello_omp
export OMP_NUM_THREADS=8
./hello_omp
 

• Line 1: Include omp.h to have libraries that support OpenMP.
• Line 7: Declare the beginning of the parallel region. Pay attention to how the curly bracket is setup, comparing to the other curly brackets.
• Line 10: omp_get_thread_num gets the ID assigned to the thread and then assign it to a variable named tid of type int.
• Line 15: omp_get_num_threads gets the value assigned to OMP_NUM_THREADS and return it to a variable named nthreads of type int.

What’s important?

• tid and nthreads.
• They allow us to coordinate the parallel workloads.
• Specify the environment variable OMP_NUM_THREADS.

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export OMP_NUM_THREADS=4
 

Trapezoid

Overview

• Problem: estimate the integral of $y=x^2$ on $[2,8]$ using trapezoidal rule. four threads.
• With 4 threads: nthreads=4.
  • How to decide which thread will handle which segment?
  • How to get all results back together?

Implementation

• Inside your csc466 directory, create a file called trapezoid.c with the following contents:

c linenums="1" --8<-- "docs/csc466/lectures/data/openmp/trapezoid_openmp_1.c"

• Compile and run trapezoid.c.

A bit more detailed

• Modify the trapezoid.c so that it looks like below.

c linenums="1" --8<-- "docs/csc466/lectures/data/openmp/trapezoid_openmp_2.c"

Challenge 1:

Alternate the trapezoid.c code so that the parallel region will invokes a function to calculate the partial sum.

```c linenums=”1” –8<– “docs/csc466/lectures/data/openmp/trapezoid_openmp_template.c”

Solution

c linenums="1" --8<-- "docs/csc466/lectures/data/openmp/trapezoid_openmp_3.c"

Challenge 2:

• Write a program called sum_series_1.c that takes a single integer N as a command line argument and calculate the sum of the first N non-negative integers.
• Speed up the summation portion by using OpenMP.
• Assume N is divisible by the number of threads.

Solution

c linenums="1" --8<-- "docs/csc466/lectures/data/openmp/sum_series_1.c"

Challenge 3:

• Write a program called sum_series_2.c that takes a single integer N as a command line argument and calculate the sum of the first N non-negative integers.
• Speed up the summation portion by using OpenMP.
• There is no assumtion that N is divisible by the number of threads.

Solution

c linenums="1" --8<-- "docs/csc466/lectures/data/openmp/sum_series_2.c"

Include timing

• Inside your csc466 directory, create a file called trapezoid_time.c with the following contents:

c linenums="1" --8<-- "docs/csc466/lectures/data/openmp/trapezoid_openmp_time.c"

• How’s the run time?