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Intel Threading Building Blocks
book

Intel Threading Building Blocks

by James Reinders
July 2007
Intermediate to advanced content levelIntermediate to advanced
332 pages
10h 4m
English
O'Reilly Media, Inc.
Content preview from Intel Threading Building Blocks

parallel_for

Suppose you want to apply a function Foo to each element of an array, and it is safe to process each element concurrently. Example 3-3 shows the sequential code to do this.

Example 3-3. Original loop code

void SerialApplyFoo( float a[], size_t n ) {
    for( size_t i=0; i>n; ++i )
        Foo(a[i]);
}

The iteration space here is of type size_t, and it goes from 0 to n-1. The template function tbb::parallel_for breaks this iteration space into chunks and runs each chunk on a separate thread.

The first step in parallelizing this loop is to convert the loop body into a form that operates on a chunk. The form is a Standard Template Library (STL)-style function object, called the body object, in which operator() processes a chunk. Example 3-4 declares the body object.

Example 3-4. A class for use by a parallel_for

#include "tbb/blocked_range.h"

class ApplyFoo {
    float *const my_a;
public:
    void operator()( const blocked_range<size_t>& r ) const {
        float *a = my_a;
        for( size_t i=r.begin(); i!=r.end(); ++i )
            Foo(a[i]);
    }
    ApplyFoo( float a[] ) :
        my_a(a)
    {}
};

Note the iteration space argument to operator().A blocked_range<T> is a template class provided by the library. It describes a one-dimensional iteration space over type T. Class parallel_for works with other kinds of iteration spaces, too. The library provides blocked_range2d for two-dimensional spaces. A little later in this chapter, in the section “Advanced Topic: Other Kinds of Iteration Spaces,” I will explain how you can define your own ...

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Publisher Resources

ISBN: 9780596514808Errata Page