Visible to Intel only — GUID: GUID-7FE06135-525E-4B3E-8134-851F1A9B837C
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-7FE06135-525E-4B3E-8134-851F1A9B837C
Exceptions and Cancellation
oneAPI Threading Building Blocks (oneTBB) supports exceptions and cancellation. When code inside an oneTBB algorithm throws an exception, the following steps generally occur:
The exception is captured. Any further exceptions inside the algorithm are ignored.
The algorithm is cancelled. Pending iterations are not executed. If there is oneTBB parallelism nested inside, the nested parallelism may also be cancelled as explained in Cancellation and Nested Parallelism.
Once all parts of the algorithm stop, an exception is thrown on the thread that invoked the algorithm.
As compilers evolve to support this functionality, future versions of oneTBB might throw the original exception. So be sure your code can catch either type of exception. The following example demonstrates exception handling:
#include "oneapi/tbb.h"
#include <vector>
#include <iostream>
using namespace oneapi::tbb;
using namespace std;
vector<int> Data;
struct Update {
void operator()( const blocked_range<int>& r ) const {
for( int i=r.begin(); i!=r.end(); ++i )
Data.at(i) += 1;
}
};
int main() {
Data.resize(1000);
try {
parallel_for( blocked_range<int>(0, 2000), Update());
} catch( out_of_range& ex ) {
cout << "out_of_range: " << ex.what() << endl;
}
return 0;
}The parallel_for attempts to iterate over 2000 elements of a vector with only 1000 elements. Hence the expression Data.at(i) sometimes throws an exception std::out_of_range during execution of the algorithm. When the exception happens, the algorithm is cancelled and an exception thrown at the call site to parallel_for.