Parallel Processing Model
A program containing OpenMP* API compiler
pragmasbegins execution as a single thread, called the initial thread of execution. The initial thread executes sequentially until the first parallel construct is encountered.
In the OpenMP* API, the
the extent of the parallel construct. When the initial thread encounters a parallel construct, it creates a team of threads, with the initial thread becoming the master of the team. All program statements enclosed by the parallel construct are executed in parallel by each thread in the team, including all routines called from within the enclosed statements.
omp parallelpragma defines
The statements enclosed lexically within a construct define the static extent of the construct. The dynamic extent includes all statements encountered during the execution of a construct by a thread, including all called routines.
When a thread encounters the end of a structured block enclosed by a parallel construct, the thread waits until all threads in the team have arrived. When that happens the team is dissolved, and only the master thread continues execution of the code following the parallel construct. The other threads in the team enter a wait state until they are needed to form another team. You can specify any number of parallel constructs in a single program. As a result, thread teams can be created and dissolved many times during program execution.
The following example illustrates, from a high level, the execution model for the OpenMP* constructs. The comments in the code explain the structure of each construct or section.
In routines called from within parallel constructs, you can also use
Pragmasthat are not in the static extent of the parallel construct, but are in the dynamic extent, are called orphaned
pragmasallow you to execute portions of your program in parallel with only minimal changes to the sequential version of the program. Using this functionality, you can code parallel constructs at the top levels of your program call tree and use directives to control execution in any of the called routines. For example:
This is an orphaned
since the parallel region is not lexically present in
omp forloop pragma
routine phase 1
Data Environment Controls
You can control the data environment within parallel and worksharing constructs. Using directives and data environment clauses on directives, you can privatize named global-lifetime objects by using
, or control data scope attributes by using the data environment clauses for directives that support them.
The data scope attribute clauses are:
The data copying clauses are:
You can use several
pragmaclauses to control the data scope attributes of variables for the duration of the construct in which you specify them; however, if you do not specify a data scope attribute clause on a
pragma, the behavior for the variable is determined by the default scoping rules, which are described in the OpenMP* API specification, for the variables affected by the directive.
Determining How Many Threads to Use
For applications where the workload depends on application input that can vary widely, delay the decision about the number of threads to employ until runtime when the input sizes can be examined. Examples of workload input parameters that affect the thread count include things like matrix size, database size, image/video size and resolution, depth/breadth/bushiness of tree-based structures, and size of list based structures. Similarly, for applications designed to run on systems where the processor count can vary widely, defer the number of threads to employ until application run-time when the machine size can be examined.
For applications where the amount of work is unpredictable from the input data, consider using a calibration step to understand the workload and system characteristics to aid in choosing an appropriate number of threads. If the calibration step is expensive, the calibration results can be made persistent by storing the results in a permanent place like the file system.
Avoid simultaneously using more threads than the number of processing units on the system. This situation causes the operating system to multiplex threads on the processors and typically yields sub-optimal performance.
When developing a library as opposed to an entire application, provide a mechanism whereby the user of the library can conveniently select the number of threads used by the library, because it is possible that the user has higher-level parallelism that renders the parallelism in the library unnecessary or even disruptive.
clause on parallel regions to control the number of threads employed and use the
clause on parallel regions to decide whether to employ multiple threads at all. The
routine can also be used, but it also affects parallel regions created by the calling thread. The
clause is local in its effect, so it does not impact other parallel regions. The disadvantages of explicitly setting a number of threads are:
- In a system with a large number of processors, your application will use some but not all of the processors.
- In a system with a small number of processors, your application may force over subscription that results in poor performance.
The Intel OpenMP runtime will create the same number of threads as the available number of logical processors unless you use the
omp_set_num_threadsroutine. To determine the actual limits, use
omp_get_max_active_levels(). Developers should carefully consider their thread usage and nesting of parallelism to avoid overloading the system. The
OMP_THREAD_LIMITenvironment variable limits the number of OpenMP* threads to use for the whole OpenMP* program. The
OMP_MAX_ACTIVE_LEVELSenvironment variable limits the number of active nested parallel regions.
The various binding sets describe which OpenMP constructs can be nested in which other OpenMP constructs and what effect that nesting has.
The binding region for an OpenMP construct is the enclosing region that determines the execution context and the scope of the effects of the directive:
- The binding region for anomp orderedconstruct is the innermost enclosingomp forloop region.
- The binding region for aomp taskwaitconstruct is the innermost enclosingomp taskregion.
- For all other constructs for which the binding thread set is the current team or the binding task set is the current team tasks, the binding region is the innermost enclosing region.
- For constructs for