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Hello,
the device manager shows "Intel (R) HD Graphics 4600" with Driver Version "20.19.15.4531".
I use the GPUOpenCLProject-Template from MSVS. Since I use Win10 I had to change the Windows SDK Version from 8.1 to 10.0.14393.0. I also tried different Platfrom Targets (Win32/x64), but executing the Programm always results in CL_DEVICE_NOT_FOUND:
I tried to start it from IDE with the Local Windows Debugger, with double clicking the .exe-file or with CLI. It's always this error.
I use VS2017 Enterprise with the tools from Intel Studio 2019.3.063 and the Intel Graphics Driver Verison 15.40.42.5063.
Best Regards,
Marcel
Hi MarcelLD,
Thanks for the details... What are the two platforms and devices per the platform info dialog... Can you expose the drop downs? Example:
Do you have any other accelerators on the system?
At the risk of making an erroneous prediction: I'm thinking it's more likely the article and sample template are stale and your system is fine. Per the source code, the program looks for the first platform that has a GPU device type. On the example system in the article, it finds a GPU device in the first platform interrogated so no issues are observed. On yours you may have newer or different platforms that are interrogated in a different order. It looks like the OpenCL-C kernel is still executing successfully and that the error emitted from the host API could have been programmed more clearly.
I recommend adding some cout << or printf(...) debugging and emitting detected parameters in the template program in particular if you are new to OpenCL... or breakpoint pausing and inspecting interrogation variables with the GUI debugger... hopefully it will make the picture clear quickly.
-MichaelC
Hello,
this is my platform info:
I have a Nvidia Graphics card too. But I have not installed OpenCL drivers for this card.
To check if the kernel is executed sucessfully I moved to a different test code:
#include <iostream>
#include <fstream>
#include <string>
#include <memory>
#include <vector>
#include <stdlib.h>
#define __CL_ENABLE_EXCEPTIONS
#include <CL/cl.hpp>
int main( int argc, char** argv ) {
const int N_ELEMENTS=1024*1024;
unsigned int platform_id=0, device_id=0;
try{
std::unique_ptr<int[]> A(new int[N_ELEMENTS]);
std::unique_ptr<int[]> B(new int[N_ELEMENTS]);
std::unique_ptr<int[]> C(new int[N_ELEMENTS]);
for( int i = 0; i < N_ELEMENTS; ++i ) {
A = i;
B = i;
}
// Query for platforms
std::vector<cl::Platform> platforms;
cl::Platform::get(&platforms);
// Get a list of devices on this platform
std::vector<cl::Device> devices;
platforms[platform_id].getDevices(CL_DEVICE_TYPE_GPU, &devices); // Select the platform.
// Create a context
cl::Context context(devices);
// Create a command queue
cl::CommandQueue queue = cl::CommandQueue( context, devices[device_id] ); // Select the device.
// Create the memory buffers
cl::Buffer bufferA=cl::Buffer(context, CL_MEM_READ_ONLY, N_ELEMENTS * sizeof(int));
cl::Buffer bufferB=cl::Buffer(context, CL_MEM_READ_ONLY, N_ELEMENTS * sizeof(int));
cl::Buffer bufferC=cl::Buffer(context, CL_MEM_WRITE_ONLY, N_ELEMENTS * sizeof(int));
// Copy the input data to the input buffers using the command queue.
queue.enqueueWriteBuffer( bufferA, CL_FALSE, 0, N_ELEMENTS * sizeof(int), A.get() );
queue.enqueueWriteBuffer( bufferB, CL_FALSE, 0, N_ELEMENTS * sizeof(int), B.get() );
// Read the program source
std::ifstream sourceFile("vector_add_kernel.cl");
std::string sourceCode( std::istreambuf_iterator<char>(sourceFile), (std::istreambuf_iterator<char>()));
cl::Program::Sources source(1, std::make_pair(sourceCode.c_str(), sourceCode.length()));
// Make program from the source code
cl::Program program=cl::Program(context, source);
// Build the program for the devices
program.build(devices);
// Make kernel
cl::Kernel vecadd_kernel(program, "vecadd");
// Set the kernel arguments
vecadd_kernel.setArg( 0, bufferA );
vecadd_kernel.setArg( 1, bufferB );
vecadd_kernel.setArg( 2, bufferC );
// Execute the kernel
cl::NDRange global( N_ELEMENTS );
cl::NDRange local( 256 );
queue.enqueueNDRangeKernel( vecadd_kernel, cl::NullRange, global, local );
// Copy the output data back to the host
queue.enqueueReadBuffer( bufferC, CL_TRUE, 0, N_ELEMENTS * sizeof(int), C.get() );
// Verify the result
bool result=true;
for (int i=0; i<N_ELEMENTS; i ++)
if (C !=A+B) {
result=false;
break;
}
if (result)
std::cout<< "Success!\n";
else
std::cout<< "Failed!\n";
}
catch(cl::Error err) {
std::cout << "Error: " << err.what() << "(" << err.err() << ")" << std::endl;
return( EXIT_FAILURE );
}
std::cout << "Done.\n";
return( EXIT_SUCCESS );
}
This code prints "Error clGetDeviceIDs(-1)". That the same issue. If I add "CL_DEVICE_TYPE_CPU" to "platforms[platform_id].getDevices()" this code runs perfect... but on the CPU and not on the GPU.
Best regards,
Marcel
