79 lines
1.8 KiB
Text
79 lines
1.8 KiB
Text
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namespace tf {
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/** @page fibonacci Fibonacci Number
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We study the classic problem, <em>Fibonacci Number</em>,
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to demonstrate the use of recursive task parallelism.
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@tableofcontents
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@section FibonacciNumberProblem Problem Formulation
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In mathematics, the Fibonacci numbers, commonly denoted @c F(n), form a sequence
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such that each number is the sum of the two preceding ones, starting from 0 and 1.
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<tt>0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, ...</tt>
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A common solution for computing fibonacci numbers is @em recursion.
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@code{.cpp}
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int fib(int n) {
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if(n < 2) return n;
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return fib(n-1) + fib(n-2);
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}
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@endcode
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@section RecursiveFibonacciParallelism Recursive Fibonacci Parallelism
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We use tf::Subflow to recursively compute fibonacci numbers in parallel.
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@code{.cpp}
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#include <taskflow/taskflow.hpp>
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int spawn(int n, tf::Subflow& sbf) {
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if (n < 2) return n;
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int res1, res2;
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sbf.emplace([&res1, n] (tf::Subflow& sbf) { res1 = spawn(n - 1, sbf); } )
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.name(std::to_string(n-1));
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sbf.emplace([&res2, n] (tf::Subflow& sbf) { res2 = spawn(n - 2, sbf); } )
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.name(std::to_string(n-2));
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sbf.join();
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return res1 + res2;
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}
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int main(int argc, char* argv[]) {
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int N = 5;
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int res;
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tf::Executor executor;
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tf::Taskflow taskflow("fibonacci");
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taskflow.emplace([&res, N] (tf::Subflow& sbf) { res = spawn(N, sbf); })
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.name(std::to_string(N));
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executor.run(taskflow).wait();
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taskflow.dump(std::cout);
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std::cout << "Fib[" << N << "]: " << res << std::endl;
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return 0;
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}
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@endcode
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The spawned taskflow graph for computing up to the fifth fibonacci number is shown below:
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@dotfile images/fibonacci_7.dot
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Even if recursive dynamic tasking or subflows are possible,
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the recursion depth may not be too deep or it can cause stack overflow.
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*/
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}
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