Difference between revisions of "OpenMP in Small Bites/Scoping"
OpenMP in Small Bites/Scoping
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Latest revision as of 08:54, 18 January 2021
Tutorial | |
---|---|
Title: | OpenMP in Small Bites |
Provider: | HPC.NRW
|
Contact: | tutorials@hpc.nrw |
Type: | Multi-part video |
Topic Area: | Programming Paradigms |
License: | CC-BY-SA |
Syllabus
| |
1. Overview | |
2. Worksharing | |
3. Data Scoping | |
4. False Sharing | |
5. Tasking | |
6. Tasking and Data Scoping | |
7. Tasking and Synchronization | |
8. Loops and Tasks | |
9. Tasking Example: Sudoku Solver | |
10. Task Scheduling | |
11. Non-Uniform Memory Access |
This video provides an overview on managing one of the most challenging parts of OpenMP: Data Scoping. It discusses the differences between private
, firstprivate
, lastprivate
and shared
variables and shows how to implement a scalable reduction.
Video
Quiz
1. What is the default data scoping of variable in a parallel region when this variable is declared before a parallel region?
2. What is the data scoping of the variables
a
, b
, c
and d
in the following code snippet in the parallel region? What is printed when executing the code? int a = 0;
int b = 23;
int c = -3;
# pragma omp parallel num_threads(2) private(a) reduction(+:c)
{
int d = omp_get_thread_num();
a = 42 + d;
# pragma omp critical
b = 1;
c += a + b;
}
c = c / 2;
printf("a=%d, b=%d, c=%d\n", a, b, c)
3. The following code snippet is wrong due to a missing data sharing attribute. How can you fix it?
int i, int s = 0;
# pragma omp parallel for
for (i = 1; i < 100; i++){
s = s + a[i];
}