Visible to Intel only — GUID: GUID-CD402820-3706-4FCC-AF35-164613906930
Package Contents
Parallelizing Simple Loops
Parallelizing Complex Loops
Parallelizing Data Flow and Dependence Graphs
Work Isolation
Exceptions and Cancellation
Floating-point Settings
Containers
Mutual Exclusion
Timing
Memory Allocation
The Task Scheduler
Design Patterns
Migrating from Threading Building Blocks (TBB)
Constrained APIs
Appendix A Costs of Time Slicing
Appendix B Mixing With Other Threading Packages
References
parallel_for_each Body semantics and requirements
parallel_sort ranges interface extension
TBB_malloc_replacement_log Function
Type-specified message keys for join_node
Scalable Memory Pools
Helper Functions for Expressing Graphs
concurrent_lru_cache
task_group extensions
The customizing mutex type for concurrent_hash_map
Visible to Intel only — GUID: GUID-CD402820-3706-4FCC-AF35-164613906930
Floating-point Settings
To propagate CPU-specific settings for floating-point computations to tasks executed by the task scheduler, you can use one of the following two methods:
When a task_arena or a task scheduler for a given application thread is initialized, they capture the current floating-point settings of the thread.
The task_group_context class has a method to capture the current floating-point settings.
By default, worker threads use floating-point settings obtained during the initialization of a task_arena or the implicit arena of the application thread. The settings are applied to all computations within that task_arena or started by that application thread.
For better control over floating point behavior, a thread may capture the current settings in a task group context. Do it at context creation with a special flag passed to the constructor:
task_group_context ctx( task_group_context::isolated,
task_group_context::default_traits | task_group_context::fp_settings );
Or call the capture_fp_settings method:
task_group_context ctx; ctx.capture_fp_settings();
You can then pass the task group context to most parallel algorithms, including flow::graph, to ensure that all tasks related to this algorithm use the specified floating-point settings. It is possible to execute the parallel algorithms with different floating-point settings captured to separate contexts, even at the same time.
Floating-point settings captured to a task group context prevail over the settings captured during task scheduler initialization. It means, if a context is passed to a parallel algorithm, the floating-point settings captured to the context are used. Otherwise, if floating-point settings are not captured to the context, or a context is not explicitly specified, the settings captured during the task arena initialization are used.
In a nested call to a parallel algorithm that does not use the context of a task group with explicitly captured floating-point settings, the outer-level settings are used. If none of the outer-level contexts capture floating-point settings, the settings captured during task arena initialization are used.
It guarantees that:
Floating-point settings are applied to all tasks executed within a task arena, if they are captured:
To a task group context.
During the arena initialization.
A call to a oneTBB parallel algorithm does not change the floating-point settings of the calling thread, even if the algorithm uses different settings.
NOTE:
The guarantees above apply only to the following conditions:
A user code inside a task should:
Not change the floating-point settings.
Revert any modifications.
Restore previous settings before the end of the task.
oneTBB task scheduler observers are not used to set or modify floating point settings.
Otherwise, the stated guarantees are not valid and the behavior related to floating-point settings is undefined.