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Exploring the "omp ordered" Clause: Understanding its Function and Usage
The "omp ordered" clause is a synchronization mechanism used in OpenMP to impose sequential execution within a parallel region. It guarantees that the code blocks covered by the "ordered" construct will be executed in the same order as they would in a serial loop.
How does it Work?
When threads encounter an "omp ordered" region, they enter a synchronization point. The lowest-numbered thread currently executing code outside the "ordered" region resumes execution, while other threads wait. Once the lowest-numbered thread exits the "ordered" region, the next lowest-numbered thread enters, and so on.
Thread Allocation
Contrary to concerns, the OpenMP runtime library ensures that the lowest iteration is always assigned to a thread. If none of the threads initially has the lowest iteration, the runtime redistributes iterations until one thread receives it.
Dynamic vs. Static Scheduling
The choice between dynamic and static scheduling when using the "ordered" clause depends on the code structure. Dynamic scheduling allows threads to execute iterations in any order, while static scheduling ensures that threads complete iterations sequentially.
In general, dynamic scheduling is recommended with the "ordered" clause to minimize idle time. With static scheduling and default chunk size, as described below, performance can suffer due to unnecessary waiting.
Example with Static Scheduling
Consider a code with 3 threads and 9 iterations:
<code class="cpp">#pragma omp parallel for ordered schedule(static) for (int i = 0; i < 9; ++i) { ... #pragma omp ordered v.push_back(i); }</code>
Static scheduling with default chunk size means that thread 0 processes iterations 0-2, thread 1 processes 3-5, and thread 2 processes 6-8. The "ordered" clause introduces a dependency, resulting in the following timeline:
tid List of Timeline iterations 0 0,1,2 ==o==o==o 1 3,4,5 ==.......o==o==o 2 6,7,8 ==..............o==o==o
Conclusion
The "omp ordered" clause provides sequential execution within parallel regions. It is recommended to use dynamic scheduling with "ordered" to minimize idle time. Choosing the appropriate scheduling strategy depends on the specific code structure and performance considerations.
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