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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-01BBE8C8-D706-409B-B971-9F4A1DC79609
Graph Application Categories
Most flow graphs fall into one of two categories:
Data flow graphs. In this type of graph, data is passed along the graph’s edges. The nodes receive, transform and then pass along the data messages.
Dependence graphs. In this type of graph, the data operated on by the nodes is obtained through shared memory directly and is not passed along the edges.