Simple Example: Fibonacci Numbers

This section uses computation of the nth Fibonacci number as an example. This example uses an inefficient method to compute Fibonacci numbers, but it demonstrates the basics of a task library using a simple recursive pattern. To get scalable speedup out of task-based programming, you need to specify a lot of tasks. This is typically done in Intel® TBB with a recursive task pattern.

This is the serial code:

long SerialFib( long n ) {
    if( n<2 )
        return n;
    else
        return SerialFib(n-1)+SerialFib(n-2);
}

The top-level code for the parallel task-based version is:

long ParallelFib( long n ) {
    long sum;
    FibTask& a = *new(task::allocate_root()) FibTask(n,&sum);
    task::spawn_root_and_wait(a);
    return sum;
}

This code uses a task of type FibTask to do the real work. It involves the following distinct steps:

  1. Allocate space for the task. This is done by a special "overloaded new" and method task::allocate_root. The _root suffix in the name denotes the fact that the task created has no parent. It is the root of a task tree. Tasks must be allocated by special methods so that the space can be efficiently recycled when the task completes.

  2. Construct the task with the constructor FibTask(n,&sum) invoked by new. When the task is run in step 3, it computes the nth Fibonacci number and stores it into *sum.

  3. Run the task to completion with task::spawn_root_and_wait.

The real work is inside struct FibTask. Its definition is shown below.

class FibTask: public task {
public:
    const long n;
    long* const sum;
    FibTask( long n_, long* sum_ ) :
        n(n_), sum(sum_)
    {}
    task* execute() {      // Overrides virtual function task::execute
        if( n<CutOff ) {
            *sum = SerialFib(n);
        } else {
            long x, y;
            FibTask& a = *new( allocate_child() ) FibTask(n-1,&x);
            FibTask& b = *new( allocate_child() ) FibTask(n-2,&y);
            // Set ref_count to 'two children plus one for the wait".
            set_ref_count(3);
            // Start b running.
            spawn( b );
            // Start a running and wait for all children (a and b).
            spawn_and_wait_for_all(a);
            // Do the sum
            *sum = x+y;
        }
        return NULL;
    }
};

It is a relatively large piece of code, compared to SerialFib, because it expresses parallelism without the help of any extensions to standard C++.

Like all tasks scheduled by Intel® TBB, FibTask is derived from class task. Fields n and sum hold respectively the input value and pointer to the output. These are copies of the arguments passed to the constructor for FibTask. Method execute does the actual computation. Every task must provide a definition of execute that overrides the pure virtual method task::execute. The definition should do the work of the task, and return either NULL, or a pointer to the next task to run. In this simple example, it returns NULL. For more information on the non-NULL case see Scheduler Bypass.

Method FibTask::execute()does the following:

At first glance, the parallelism might appear to be limited, because the task creates only two child tasks. The trick here is recursive parallelism. The two child tasks each create two child tasks, and so on, until n<Cutoff. This chain reaction creates a lot of potential parallelism. The advantage of the task scheduler is that it turns this potential parallelism into real parallelism in a very efficient way, because it chooses tasks to run in a way that keeps physical threads busy with relatively little context switching.

See Also