Using Double Precision with GTX 260 double precision issue

Accelerated Computing CUDA CUDA Programming and Performance
1

Hi

I am trying to run double precision with my GTX 260 and CUDA 2.3 (latest greatest). However I am running into some issues.

This is the simple code that squares each element in an array with CUDA

// example1.cpp : Defines the entry point for the console application.

//

#include <stdio.h>

#include <stdlib.h>

#include <cuda_runtime.h>

#include <cutil.h>

// Kernel that executes on the CUDA device

__global__ void square_array(double *a, int N)

{

  int idx = blockIdx.x * blockDim.x + threadIdx.x;

  if (idx<N) a[idx] = a[idx] * a[idx];

}

// main routine that executes on the host

int main(void)

{

  double *a_h, *a_d;  // Pointer to host & device arrays

  const int N = 10;  // Number of elements in arrays

  size_t size = N * sizeof(double);

a_h = (double *)malloc(size);		// Allocate array on host

  cudaMalloc((void **) &a_d, size);   // Allocate array on device

// Initialize host array and copy it to CUDA device

  for (int i=0; i<N; i++) a_h[i] = (double)i;

  cudaMemcpy(a_d, a_h, size, cudaMemcpyHostToDevice);

// Do calculation on device:

  int block_size = 4;

  int n_blocks = N/block_size + (N%block_size == 0 ? 0:1);

  square_array <<< n_blocks, block_size >>> (a_d, N);

  cudaError_t result = cudaGetLastError();

if (result != cudaSuccess)

	printf("oh no everything is ruined forever--the kernel didn't even launch\n");

result = cudaThreadSynchronize();

if (result != cudaSuccess)

	printf("oh no now the kernel itself broke in the middle of execution\n");

// Retrieve result from device and store it in host array

  cudaMemcpy(a_h, a_d, sizeof(double)*N, cudaMemcpyDeviceToHost);

// Print results

  for (int i=0; i<N; i++) printf("%d %f\n", i, a_h[i]);

  // Cleanup

  free(a_h); cudaFree(a_d);

  getchar();

	return 0;

}

I installed the CUDA VS Wizard 2.0 so I basically just create a New Project in VS and I select “1.3 (hardware) Arch” and “1.3 (hardware) code” for the GPU architecture but when I run the code, I get:

1>nvcc fatal   : Value of -arch option ('sm_13') must be a virtual code architecture

So then I change the GPU architecture to “1.3 (virtual) Arch” and “1.3 (virtual) code”, and the code complies and the answer is right

Questions:

  1. why doesnt hardware option work? I have a GTX 260 it should support it?

  2. does that mean i am emulating and not actually running on the GPU?? (i am noob)

Please help!

2

You can use the datatype double with your GTX 260.

I have tested the code on my GXT275 and what should I say it works.