opencl

CUDA 5 has just been released and with it the ability to spawn GPU threads from within another GPU (main?) thread, minimising callouts between CPU and GPU that we've seen thus far. What plans are there to support GPU-spawned threads in the OpenCL arena? As I cannot afford to opt for a closed standard (my user base is "everygamer"), I need to know when OpenCL is ready for prime time in this regard. OpenCL Standard is usually the way back of CUDA (except for device partitioning feature) and I guess this feature will be added to OpenCL in a year. EDIT on Aug 8, 2013: This feature has been

I have multiple kernels, and they are launched in sequential manner like this: clEnqueueNDRangeKernel(..., kernel1, ...); clEnqueueNDRangeKernel(..., kernel2, ...); clEnqueueNDRangeKernel(..., kernel3, ...); and, multiple kernels share one global buffer. Now, I profile every kernel execution and sum them up to count total execution time by adding the code block after clEnqueueNDRangeKernel: clFinish(cmdQueue); status = clGetEventProfilingInfo(...,&starttime,...); clGetEventProfilingInfo(...,&endtime,...); time_spent = endtime - starttime; My questions is that how to profile three kernels all

I want to use 2 OpenCL runtimes in one system together (in my case AMD and Nvidia, but the question is pretty generic). I know that I can compile my program with any SDK. But when running the program, I need to provide libOpenCL.so. How can I provide the libs of both runtimes so that I see 3 devices (AMD CPU, AMD GPU, Nvidia GPU) in my OpenCL program? I know that it must be possible somehow, but I didn't find a description on how to do it for linux, yet. Thanks a lot, Tomas The Smith and Thomas answers are correct; this is just expanding on that information: When you enumerate the OpenCL

I have a OpenCL kernel that needs to process a array as multiple arrays where each sub-array sum is saved in a local cache array. For example, imagine the fowling array: [[1, 2, 3, 4], [10, 30, 1, 23]] Each work-group gets a array (in the exemple we have 2 work-groups); Each work-item process two array indexes (for example multiply the value index the local_id), where the work-item result is saved in a work-group shared array. __kernel void test(__global int **values, __global int *result, const int array_size){ __local int cache[array_size]; // initialise if (get_local_id(0) == 0){ for (int i

I am working on a project that needs a lot of OpenCL code. I am using OpenCV's ocl module to develop my project faster but there are some functions not implemented and I will have to write my own OpenCL code. My question is this: what is the quickest and cheapest way to transfer data from Mat and/or oclMat to a cl_mem array. Re-wording this, is there a good way to transfer or enqueue (clEnqueueWriteBuffer) data from oclMat or Mat? Currently, I am using a for-loop to read data from Mat (or download from oclMat and then use for-loops) and then enqueuing it. This is turning out to be costly,

I've written an OpenCL kernel in a .cl file. It attempts to #include several headers. Its compilation fails, since the included header files are "not found". I am aware that clBuildProgram can take the -I dir option, which adds the directory dir to the list of directories to be searched for the header files. In the khronus site forum this post http://www.khronos.org/message_boards/viewtopic.php?f=37&t=2535 talks about the issue. They propose to use clCreateProgramWithSource which specifies all sources (including .h files). I have a questions regarding this issue: Which option is better? (

Is there any way to debug OpenCL kernels on an Nvidia GPU, i.e. set breakpoints and inspect variables? My understanding is that Nvidia's tool does not allow OpenCL debugging, and AMD's and Intel's only allow it on their own devices. gDEBugger might help you somewhat (never used it though), but other than that there isn't any tool that I know of that can set breakpoints or inspect variables inside a kernel. Perhaps try to save intermediate outputs from your kernel if it is a long kernel. Sorry I can't give you a magic solution, debugging OpenCL is just hard. 来源： https://stackoverflow.com

I've been playing with the ATI OpenCL implementation in their Stream 2.0 beta. The OpenCL in the current beta only uses the CPU for now, the next version is supposed to support GPU kernels. I downloaded Stream because I have an ATI GPU in my work machine. I write software that would benefit hugely from gains by using the GPU. However this software runs on customer machines, I don't have the luxury (as many scientific computing environments have) to choose the exact hardware to develop for, and optimize for that. So my question is, if I distribute the ATI OpenCL implementation with my