Visible to Intel only — GUID: GUID-6E3F09C3-B229-4031-AC33-7480CF180377
Package Contents
Parallelizing Simple Loops
Parallelizing Complex Loops
Parallelizing Data Flow and Dependence Graphs
Work Isolation
Exceptions and Cancellation
Containers
Mutual Exclusion
Timing
Memory Allocation
The Task Scheduler
Design Patterns
Migrating from Threading Building Blocks (TBB)
Constrained APIs
Invoke a Callable Object
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
Parallel Reduction for rvalues
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
Waiting for Single Messages in Flow Graph
Visible to Intel only — GUID: GUID-6E3F09C3-B229-4031-AC33-7480CF180377
Containers
oneAPI Threading Building Blocks (oneTBB) provides highly concurrent container classes. These containers can be used with raw Windows* OS or Linux* OS threads, or in conjunction with task-based programming.
A concurrent container allows multiple threads to concurrently access and update items in the container. Typical C++ STL containers do not permit concurrent update; attempts to modify them concurrently often result in corrupting the container. STL containers can be wrapped in a mutex to make them safe for concurrent access, by letting only one thread operate on the container at a time, but that approach eliminates concurrency, thus restricting parallel speedup.
Containers provided by oneTBB offer a much higher level of concurrency, via one or both of the following methods:
Fine-grained locking: Multiple threads operate on the container by locking only those portions they really need to lock. As long as different threads access different portions, they can proceed concurrently.
Lock-free techniques: Different threads account and correct for the effects of other interfering threads.
Notice that highly-concurrent containers come at a cost. They typically have higher overheads than regular STL containers. Operations on highly-concurrent containers may take longer than for STL containers. Therefore, use highly-concurrent containers when the speedup from the additional concurrency that they enable outweighs their slower sequential performance.
CAUTION:
As with most objects in C++, the constructor or destructor of a container object must not be invoked concurrently with another operation on the same object. Otherwise the resulting race may cause the operation to be executed on an undefined object.