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#include <thrust/transform_reduce.h>
#include <thrust/functional.h>
#include <thrust/device_vector.h>
#include <thrust/host_vector.h>
#include <cmath>
#include <iostream>
// This example computes the norm [1] of a vector. The norm is
// computed by squaring all numbers in the vector, summing the
// squares, and taking the square root of the sum of squares. In
// Thrust this operation is efficiently implemented with the
// transform_reduce() algorith. Specifically, we first transform
// x -> x^2 and the compute a standard plus reduction. Since there
// is no built-in functor for squaring numbers, we define our own
// square functor.
//
// [1] http://en.wikipedia.org/wiki/Norm_(mathematics)#Euclidean_norm
// square<T> computes the square of a number f(x) -> x*x
template <typename T>
struct square
{
__host__ __device__
T operator()(const T& x) const {
return x * x;
}
};
int main(void)
{
// initialize host array
float x[4] = {1.0, 2.0, 3.0, 4.0};
// transfer to device
thrust::device_vector<float> d_x(x, x + 4);
// setup arguments
square<float> unary_op;
thrust::plus<float> binary_op;
float init = 0;
// compute norm
float norm = std::sqrt( thrust::transform_reduce(d_x.begin(), d_x.end(), unary_op, init, binary_op) );
std::cout << "norm is " << norm << std::endl;
return 0;
}