How to normalise a vector with thrust? - normalization

Question

I am learning the thrust for the moment. I have a question: how to normalise with thrust?
I have a code that works, but I want to know if this is the optimum method.
struct square
{
__host__ __device__
float operator() (float x)
{
return x * x;
}
};
thrust::device_vector<float> d_x(2);
thrust::device_vector<float> d_y(2);
thrust::device_vector<float> d_z(2);
d_x[0] = 3;
d_x[1] = 4;
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) );
thrust::fill(d_y.begin(), d_y.end(), 1/norm);
thrust::transform(d_x.begin(), d_x.end(), d_y.begin(), d_z.begin(), thrust::multiplies<float>());

Answer 1

This should be more efficient because it does not need to use for storage or bandwidth for d_y or d_z:
#include <thrust/device_vector.h>
#include <thrust/inner_product.h>
#include <thrust/transform.h>
#include <thrust/functional.h>
#include <cmath>
int main()
{
thrust::device_vector<float> d_x(2);
d_x[0] = 3;
d_x[1] = 4;
float norm = std::sqrt(thrust::inner_product(d_x.begin(), d_x.end()));
using namespace thrust::placeholders;
thrust::transform(d_x.begin(), d_x.end(), d_x.begin(), _1 /= norm);
return 0;
}
You'll want to make your problem size a few orders of magnitude larger, of course.