opencl

I have seen both versions in tutorials, but I could not find out, what their advantages and disadvantages are. Which one is the proper one? cl_mem input = clCreateBuffer(context,CL_MEM_READ_ONLY,sizeof(float) * DATA_SIZE, NULL, NULL); clEnqueueWriteBuffer(command_queue, input, CL_TRUE, 0, sizeof(float) * DATA_SIZE, inputdata, 0, NULL, NULL); vs. cl_mem input = clCreateBuffer(context,CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, ,sizeof(float) * DATA_SIZE, inputdata, NULL); Thanks. [Update] I added CL_MEM_COPY_HOST_PTR, to the second example to make it correct. I assume that inputdata is not NULL.

As known, OpenCV 3.0 supports new class cv::Umat which provides Transparent API (TAPI) to use OpenCL automaticaly if it can: http://code.opencv.org/projects/opencv/wiki/Opencv3#tapi There are two indtroductions to the cv::Umat and TAPI: Intel: https://software.intel.com/en-us/articles/opencv-30-architecture-guide-for-intel-inde-opencv AMD: http://developer.amd.com/community/blog/2014/10/15/opencv-3-0-transparent-api-opencl-acceleration/ But if I have: Intel CPU Core i5 (Haswell) 4xCores (OpenCL Intel CPUs with SSE 4.1, SSE 4.2 or AVX support ) Intel Integrated HD Graphics which supports OpenCL

I am using ATI RV770 graphics card, OpenCl 1.0 and ati-stream-sdk-v2.3-lnx64 on linux. While running my host code which includes following two sections to build kernel program, i am getting error code (-11) i.e. cl_build_program_failure . Does it means that kernel program compiled, if not then how is it compiled and debugged? const char* KernelPath = "abc_kernel.cl"; //kernel program is in separate file but in same directory of host code.. / * Create Program object from the kernel source * ** * ** * / char* sProgramSource = readKernelSource(KernelPath); size_t sourceSize = strlen

After finally managing to get my code to compile with OpenCL, I cannot seem to get the output binary to run! This is on my linux laptop running Kubuntu 13.10 x64 The error I get is (Printed from cl::Error): ERROR: clGetPlatformIDs -1001 I found this post but there does not seem to be a clear solution. I added myself to the video group but this does not seem to work. With regards to the ICD profile... I am not sure what I need to do - shouldn't this be included with the cuda toolkit? If not, where could I download one? EDIT : It seems I have an ICD file in my system under /usr/share/nvidia-331

I was working on a kernel which had much global memory access per thread so I copied them to local memory which gave a speed up of 40%. I wanted still more speed up so copied from local to private which degraded the performance So is it correct that I think we must not use to much private memory which may degrade the performance? Ashwin's answer is in the right direction but a little misleading. OpenCL abstracts the address space of variables away from their physical storage, and there is not necessarily a 1:1 mapping between the two. Consider OpenCL variables declared in the __private address

I have a variable whithin a kernel like: int16 element; I would like to know if there is a way to adress the third int in element like element[2] so that i would be as same as writing element.s2 So how can i do something like: int16 element; int vector[100] = rand() % 16; for ( int i=0; i<100; i++ ) element[ vector[i] ]++; The way i did was: int temp[16] = {0}; int16 element; int vector[100] = rand() % 16; for ( int i=0; i<100; i++ ) temp[ vector[i] ]++; element = (int16)(temp[0],temp[1],temp[2],temp[3],temp[4],temp[5],temp[6],temp[7],temp[8],temp[9],temp[10],temp[11],temp[12],temp[13],temp[14