CUDA 4.1 with Visual Studio 2012


Every time I install a newer version of Visual Studio, I want to be able to use it for all my projects and Visual Studio 2012 was not exception.

But, just like with the older versions you need to customize and setup the IDE so it can compile and run CUDA C programs.

Below is a quick and easy guide for doing just that, it’s pretty much the same as for VS2010, so if you are already familiar with it, it will even more easier to follow.


First of all you need to make sure you already have the CUDA Toolkit, SDK and Drivers installed.

  1. Open up VS2012 and go to Tools->Options->Text Editor->File Extension
  2. Add a new extension for cu and select Microsoft Visual C++ as an Editor
  3. Copy C:\Users\<User>\AppData\Local\NVIDIA Corporation\NVIDIA GPU Computing SDK 4.0\C\doc\syntax_highlighting\visual_studio_8\usertype.dat to C:\Program Files (x86)\Microsoft Visual Studio 11.0\Common7\IDE (this will add syntax highlithing to the CUDA C language keywords, like __global__ and __device__)


Start by creating something simple like console application and follow the next steps:

  1. Right Click on the Project at the Solution Explorer and Select Build Customizations…
  2. You should now see a list of configuration files but none of them are for CUDA. So you must click on Find Existing button and add the CUDA target files located at C:\Program Files (x86)\MSBuild\Microsoft.Cpp\v4.0\BuildCustomizations
  3. Select one of the CUDA configuration files and click Ok.
  4. Add a new cpp source file and change it’s extension to .cu
  5. Open the file’s Properties(Alt+Enter) and change it’s Configuration Properties->General->Item type to CUDA C/C++
  6. Now, go to the project’s property page and add the following Additional Dependency cudart.lib to the Linker’s Input. (Configuration Properties->Linker->Input->Additional Dependency)
  7. Finally, still at the project’s properties page change Configuration Properties->General->Platform Toolset to Visual Studio 2010 (v100)


You can add the following code to the source file to test if Visual Studio is ready.

This is a very simplistic program, it displays some information about your CUDA devices and sums 2 vectors on just 10 blocks with 1 thread each.

#include <iostream>
#include <cuda_runtime.h>

#define N 10
#define CUDA_ERROR 1

__global__ void add( int *a, int *b, int *c ) {
	int tid = blockIdx.x;

	if(tid < N)
		c[tid] = a[tid] + b[tid];

int main( void ) {
	int count;
	cudaDeviceProp prop;

	int a[N], b[N], c[N];
	int *dev_a, *dev_b, *dev_c;

	if( cudaGetDeviceCount(&count) != cudaSuccess)
		return CUDA_ERROR;

	for(int i = 0; i < count; i++) {
		if(cudaGetDeviceProperties(&prop, i) != cudaSuccess)
			return CUDA_ERROR;

		printf("--- General Information for device %d ---\n", i);
		printf("Name: %s\n",;
		printf("Compute capability: %d.%d\n", prop.major, prop.minor);
		printf("Max threads per block: %d\n", prop.maxThreadsPerBlock);
		printf("Max thread dimensions: (%d, %d, %d)\n",
		printf("Max grid dimensions; (%d, %d, %d)\n",

	cudaMalloc((void**)&dev_a, N * sizeof(int));
	cudaMalloc((void**)&dev_b, N * sizeof(int));
	cudaMalloc((void**)&dev_c, N * sizeof(int));

	printf("\n\n--- Adding 2 vectors on the GPU ---\n");
	for(int i = 0; i < N; i++) {
		a[i] = i * 2;
		b[i] = i * i;

	cudaMemcpy(dev_a, a, N * sizeof(int), cudaMemcpyHostToDevice);
	cudaMemcpy(dev_b, b, N * sizeof(int), cudaMemcpyHostToDevice);

	add<<<N, 1>>>(dev_a, dev_b, dev_c);

	cudaMemcpy( c, dev_c, N * sizeof(int), cudaMemcpyDeviceToHost );

	for(int i = 0; i < N; i++) {
		printf("%d + %d = %d\n", a[i], b[i], c[i]);

	cudaFree( dev_a );
	cudaFree( dev_b );
	cudaFree( dev_c );

	return 0;


This is the result I get. Yours may yield different values for the device’s properties.

--- General Information for device 0 ---
Name: GeForce GT 240M
Compute capability: 1.2
Max threads per block: 512
Max thread dimensions: (512, 512, 64)
Max grid dimensions; (65535, 65535, 1)
--- Adding 2 vectors on the GPU ---
0 + 0 = 0
2 + 1 = 3
4 + 4 = 8
6 + 9 = 15
8 + 16 = 24
10 + 25 = 35
12 + 36 = 48
14 + 49 = 63
16 + 64 = 80
18 + 81 = 99

15 thoughts on “CUDA 4.1 with Visual Studio 2012

  1. sian November 7, 2012 / 19:03

    really helped me, worked with cuda 5.0 as well
    good job 🙂

  2. joe November 14, 2012 / 16:34

    need help for configuration with cuda 5.0. project configuration does not have cuda target file

  3. hruivo November 15, 2012 / 18:23

    joe, what’s you machine’s architecture? 32 or 64 bits?
    Your’s may be at C:\Program Files\MSBuild\Microsoft.Cpp\v4.0\BuildCustomizations instead.
    Besides that, did you installed all the necessary software?

  4. Piotr December 2, 2012 / 12:58

    ehh I tried it but I fail in IDE configuration 3 when I copy it doesn’t work;s
    and next I can’t chose Item type to CUDA C/C++ ;s please contact me. I will be glad if you help me fix it

    • hruivo December 2, 2012 / 15:39

      Hi, are you sure that you added a new extension for the cu file type and select Microsoft Visual C++ as an Editor?
      And try restarting the IDE before you start configuring the project.

      Let me know if the problem still persists.

    • hruivo December 2, 2012 / 23:37

      those are intellisense errors. intellisense doesn’t know how to handle the cuda C language keywords.
      I can’t help you on that, I also dont know how to make visual studio to ignore them 😉

      • Piotr December 3, 2012 / 00:35

        thanks a lot you’r very good and only one person who show how to use cuda on vs2012 thanks a lot and good luck. Great portfolio.

      • hruivo December 3, 2012 / 15:02

        Thank you! And you are welcome 😉

  5. tommyHU January 21, 2013 / 08:08

    It did work when selecting Visual Studio 2010 (v100) Toolset. But do you know how to make it work with Visual Studio 2012 (v110) Toolset? This is more natural, right?

  6. Linus March 11, 2013 / 17:36

    Awesome! Thanks!

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