Simple OpenCL Example from OpenCL_GettingStartedLinux.pdf wrong output - only zeros

Hello together!

I’m very lucky about the fact that I can use the quite new OpenCL implementation from Nvidia and that there are so many code examples and docs which help me as someone without any prior knowledge about OpenCL or CUDA to understand this topic. Many thanks for that!

So I’ve read the OpenCL_GettingStartedLinux.pdf from the NVDeveloper homepage and installed this stuff on my OpenSUSE 11.0 system:

[font=“Courier New”][/font]

After compilation I could run oclDeviceQuery and the output was correct.

Then I’ve compiled the nice example from the OpenCL_GettingStartedLinux.pdf (appended) but the output was “empty”. So I decided to output the values of the HostOutputVector as integers and there are only zeros instead of the sum of the two other vectors:

[font=“Courier New”] > ./vectoradd



00000000000000000000 00000000000000000000 00000000000000000000 00000000000000000000 00000000000000000000


The End[/font]

I only added the output about the driver and the device to see if it’s right and it is.

Am I doing something wrong? Many thanks for your help!

Best regards,


That’s the code. I couldn’t attach it as a file…


// Demo OpenCL application to compute a simple vector addition

// computation between 2 arrays on the GPU

// ************************************************************

#include <stdio.h>

#include <stdlib.h>

#include <CL/cl.h>

// OpenCL source code

const char* OpenCLSource = {

   "__kernel void VectorAdd(__global int* c, __global int* a,__global int* B)",


   "	  // Index of the elements to add \n",

   "	  unsigned int n = get_global_id(0);",

   "	  // Sum the n’th element of vectors a and b and store in c \n",

   "	  c[n] = a[n] + b[n];",



// Some interesting data for the vectors

int InitialData1[20] = {37,50,54,50,56,0,43,43,74,71,32,36,16,43,56,100,50,25,15,17


int InitialData2[20] = {35,51,54,58,55,32,36,69,27,39,35,40,16,44,55,14,58,75,18,15


// Number of elements in the vectors to be added

#define SIZE 2048

// Main function

// ************************************************************

int main(int argc, char **argv)


// Two integer source vectors in Host memory

int HostVector1, HostVector2;

// Initialize with some interesting repeating data

for(int c = 0; c < SIZE; c++)


 HostVector1[c] = InitialData1[c%20];

 HostVector2[c] = InitialData2[c%20];


//Get an OpenCL platform

cl_platform_id cpPlatform;

clGetPlatformIDs(1, &cpPlatform, NULL);

// Get a GPU device

cl_device_id cdDevice;

clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, 1, &cdDevice, NULL);

char cBuffer[1024];

clGetDeviceInfo(cdDevice, CL_DEVICE_NAME, sizeof(cBuffer), &cBuffer, NULL);

printf(“CL_DEVICE_NAME: %s\n”, cBuffer);

clGetDeviceInfo(cdDevice, CL_DRIVER_VERSION, sizeof(cBuffer), &cBuffer, NULL);

printf(“CL_DRIVER_VERSION: %s\n\n”, cBuffer);

// Create a context to run OpenCL on our CUDA-enabled NVIDIA GPU

cl_context GPUContext = clCreateContextFromType(0, CL_DEVICE_TYPE_GPU, NULL, NULL, NULL);

// Create a command-queue on the GPU device

cl_command_queue cqCommandQueue = clCreateCommandQueue(GPUContext, cdDevice, 0, NULL);

// Allocate GPU memory for source vectors AND initialize from CPU memory

cl_mem GPUVector1 = clCreateBuffer(GPUContext, CL_MEM_READ_ONLY |

			CL_MEM_COPY_HOST_PTR, sizeof(int) * SIZE, HostVector1, NULL);

cl_mem GPUVector2 = clCreateBuffer(GPUContext, CL_MEM_READ_ONLY |

			 CL_MEM_COPY_HOST_PTR, sizeof(int) * SIZE, HostVector2, NULL);

// Allocate output memory on GPU

cl_mem GPUOutputVector = clCreateBuffer(GPUContext, CL_MEM_WRITE_ONLY,

								sizeof(int) * SIZE, NULL, NULL);

// Create OpenCL program with source code

cl_program OpenCLProgram = clCreateProgramWithSource(GPUContext, 7,

			  OpenCLSource, NULL, NULL);

// Build the program (OpenCL JIT compilation)

clBuildProgram(OpenCLProgram, 0, NULL, NULL, NULL, NULL);

// Create a handle to the compiled OpenCL function (Kernel)

cl_kernel OpenCLVectorAdd = clCreateKernel(OpenCLProgram, “VectorAdd”, NULL);

// In the next step we associate the GPU memory with the Kernel arguments

clSetKernelArg(OpenCLVectorAdd, 0, sizeof(cl_mem), (void*)&GPUOutputVector);

clSetKernelArg(OpenCLVectorAdd, 1, sizeof(cl_mem), (void*)&GPUVector1);

clSetKernelArg(OpenCLVectorAdd, 2, sizeof(cl_mem), (void*)&GPUVector2);

// Launch the Kernel on the GPU

size_t WorkSize[1] = {SIZE}; // one dimensional Range

clEnqueueNDRangeKernel(cqCommandQueue, OpenCLVectorAdd, 1, NULL,

					 WorkSize, NULL, 0, NULL, NULL);

// Copy the output in GPU memory back to CPU memory

int HostOutputVector;

clEnqueueReadBuffer(cqCommandQueue, GPUOutputVector, CL_TRUE, 0,

				  SIZE * sizeof(int), HostOutputVector, 0, NULL, NULL);

// Cleanup








// Print out the results

for (int Rows = 0; Rows < (SIZE/20); Rows++, printf("\t")){

  for(int c = 0; c <20; c++){

	  printf("%d",HostOutputVector[Rows * 20 + c]);



printf("\n\nThe End\n\n");

return 0;


Hello again!

I didn’t have the time before but now (after the bad football match for our German team :’-( ) I’ve checked the error values and I’ve seen that the following line from the example code:
[font=“Courier New”]cl_context GPUContext = clCreateContextFromType(0, CL_DEVICE_TYPE_GPU, NULL, NULL, NULL);[/font]
returns the following error code:
[font=“Courier New”]-32 == CL_INVALID_PLATFORM[/font]

I don’t know why but I changed the line to the following:
[font=“Courier New”]cl_context GPUContext = clCreateContext(0, 1, &cdDevice, NULL, NULL, NULL);[/font]

Now all works fine but that means that either the example from NVidia’s PDF file is wrong or the implementation of [font=“Courier New”]clCreateContextFromType[/font] is buggy. I don’t know - I’m a newbie…
Maybe someone of you know if and where it must be reported.

Best regards,

The example is wrong, it’s illegal to create a context without supplying a platform id.

It was once considered legal to pass a NULL instead but no longer. They’ve probably forgot to update it.

Thanks for this information! Then I feal reassured, that it’s not the OpenCL-implementation… :thanks: