thrust

I just write an simple CUDA Thrust program, but when I run it. I got this error: thrust::system::system_error at position 0x0037f99c . Can someone help me to figure out why this happen? #include<thrust\host_vector.h> #include<thrust\device_vector.h> #include<iostream> using namespace std; using namespace thrust; int main() { thrust::host_vector<int> h_vec(3); h_vec[0]=1;h_vec[1]=2;h_vec[2]=3; thrust::device_vector<int> d_vec(3) ; d_vec= h_vec; int h_sum = thrust::reduce(h_vec.begin(), h_vec.end()); int d_sum = thrust::reduce(d_vec.begin(), d_vec.end()); return 0; } Robert Crovella A few

I'm trying to pass device_vector of structures struct point { unsigned int x; unsigned int y; } to a function in a following manner: void print(thrust::device_vector<point> &points, unsigned int index) { std::cout << points[index].y << points[index].y << std::endl; } myvector was initialized properly print(myvector, 0); I get following errors: error: class "thrust::device_reference<point>" has no member "x" error: class "thrust::device_reference<point>" has no member "y" What's wrong with it? Unfortunately, device_reference<T> cannot expose members of T , but it can convert to T . To implement

Is it possible to leave the return value of a thrust::reduce operation in device-allocated memory? In case it is, is it just as easy as assigning the value to a cudaMalloc'ed area, or should I use a thrust::device_ptr? Is it possible to leave the return value of a thrust::reduce operation in device-allocated memory? The short answer is no. thrust reduce returns a quantity, the result of the reduction. This quantity must be deposited in a host resident variable : Take for example reduce, which is synchronous and always returns its result to the CPU: template<typename Iterator, typename T> T

I am trying to solve a problem using CUDA Thrust. I have a host array with 3 elements. Is it possible, using Thrust, to create a device array of 384 elements in which the 3 elements in my host array is repeated 128 times ( 128 x 3 = 384 )? Generally speaking, starting from an array of 3 elements, how can I use Thrust to generate a device array of size X , where X = Y x 3 , i.e. Y is the number of repetitions? One possible approach: create a device vector of appropriate size create 3 strided ranges , one for each of the element positions {1, 2, 3} in the final output (device) vector use thrust:

I'm evaluating CUDA and currently using Thrust library to sort numbers. I'd like to create my own comparer for thrust::sort, but it slows down drammatically! I created my own less implemetation by just copying code from functional.h . However it seems to be compiled in some other way and works very slowly. default comparer: thrust::less() - 94 ms my own comparer: less() - 906 ms I'm using Visual Studio 2010. What should I do to get the same performance as at option 1? Complete code: #include <stdio.h> #include <cuda.h> #include <thrust/host_vector.h> #include <thrust/device_vector.h> #include

I have a fairly simple problem but I cannot figure out an elegant solution to it. I have a Thrust code which produces c vectors of same size containing values. Let say each of these c vectors have an index. I would like for each vector position to get the index of the c vector for which the value is the lowest: Example: C0 = (0,10,20,3,40) C1 = (1,2 ,3 ,5,10) I would get as result a vector containing the index of the C vector which has the lowest value: result = (0,1 ,1 ,0,1) I have thought about doing it using thrust zip iterators, but have come accross issues: I could zip all the c vectors

I would like to copy memory from the host to the device using thrust as in thrust::host_vector<float> h_vec(1 << 28); thrust::device_vector<float> d_vec(1 << 28); thrust::copy(h_vec.begin(), h_vec.end(), d_vec.begin()); using CUDA streams analogously to how you would copy memory from the device to the device using streams: cudaStream_t s; cudaStreamCreate(&s); thrust::device_vector<float> d_vec1(1 << 28), d_vec2(1 << 28); thrust::copy(thrust::cuda::par.on(s), d_vec1.begin(), d_vec1.end(), d_vec2.begin()); cudaStreamSynchronize(s); cudaStreamDestroy(s); The problem is that I can't set the