Visible to Intel only — GUID: GUID-0FCB19D5-9EC1-4AE1-A3ED-CFB5DB64D08C
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-0FCB19D5-9EC1-4AE1-A3ED-CFB5DB64D08C
Advanced Example
An example of a more advanced associative operation is to find the index where Foo(i) is minimized. A serial version might look like this:
long SerialMinIndexFoo( const float a[], size_t n ) {
float value_of_min = FLT_MAX; // FLT_MAX from <climits>
long index_of_min = -1;
for( size_t i=0; i<n; ++i ) {
float value = Foo(a[i]);
if( value<value_of_min ) {
value_of_min = value;
index_of_min = i;
}
}
return index_of_min;
}The loop works by keeping track of the minimum value found so far, and the index of this value. This is the only information carried between loop iterations. To convert the loop to use parallel_reduce, the function object must keep track of the carried information, and how to merge this information when iterations are spread across multiple threads. Also, the function object must record a pointer to a to provide context.
The following code shows the complete function object.
class MinIndexFoo {
const float *const my_a;
public:
float value_of_min;
long index_of_min;
void operator()( const blocked_range<size_t>& r ) {
const float *a = my_a;
for( size_t i=r.begin(); i!=r.end(); ++i ) {
float value = Foo(a[i]);
if( value<value_of_min ) {
value_of_min = value;
index_of_min = i;
}
}
}
MinIndexFoo( MinIndexFoo& x, split ) :
my_a(x.my_a),
value_of_min(FLT_MAX), // FLT_MAX from <climits>
index_of_min(-1)
{}
void join( const SumFoo& y ) {
if( y.value_of_min<value_of_min ) {
value_of_min = y.value_of_min;
index_of_min = y.index_of_min;
}
}
MinIndexFoo( const float a[] ) :
my_a(a),
value_of_min(FLT_MAX), // FLT_MAX from <climits>
index_of_min(-1),
{}
};Now SerialMinIndex can be rewritten using parallel_reduce as shown below:
long ParallelMinIndexFoo( float a[], size_t n ) {
MinIndexFoo mif(a);
parallel_reduce(blocked_range<size_t>(0,n), mif );
return mif.index_of_min;
}