gpgpu

I have a cuda kernel which works fine when called from a single CPU threads. However when the same is called from multiple CPU threads (~100), most of the kernel seems not be executed at all as the results comes out to be all zeros.Can someone please guide me how to resolve this problem? In the current version of kernel I am using a cudadevicesynchronize() at the end of kernel call. Will adding a sync command before cudaMalloc() and kernel call be of any help in this case? There is another thing which need some clarification. i.e. If two CPU threads executes the same cudaMalloc() command, will

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 a question regarding compute shaders. are compute shaders available in DX 9? would it be still possible to use a compute shader with a DX9 driver if there is no compute shader fragment on the GPU? ( SGX 545 does not have it, but SGX 6X generation is going to have it), as far as what IMG says. I would like to know If i can do some simple general purpose programming on SGXs GPUs with DirectX9 or OpenGL drivers. Also, is there anyway I can use OpenGL vertex shaders for GPGPU programming? Here is what I am thinking: I will load my Matrices/ data into the vertex buffer, and bind them to the

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

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