![]() ![]() ![]() dim3 blocks(data->size, data->size) float im data->im //CHANGED float re. I would be clear where the configuration of the threads has been defined, and the 1D, 2D and 3D access pattern depends on how you are interpreting your data and also how you are accessing them by 1D, 2D and 3D blocks of threads. By experimenting with the grid and block dimensions of the kernel. To sumup, it does it matter if you use a dim3 structure. Each block can execute in any order relative to other blocks. Int y = blockIdx.y * blockDim.y + threadIdx.y īecause blockIdx.y and threadIdx.y will be zero. propogateInputOnDevice (dim3 grid, dim3 block, float inputs, float weights, float outputs, int numInputs, int sequenceId, int numOutputs) Wrapper for propogateInputKernel. So, in both cases: dim3 blockDims(512) and myKernel>(.) you will always have access to threadIdx.y and threadIdx.z.Īs the thread ids start at zero, you can calculate a memory position as a row major order using also the ydimension: int x = blockIdx.x * blockDim.x + threadIdx.x The same happens for the blocks and the grid. When defining a variable of type dim3, any component left unspecified is initialized to 1. Pre-defined variables dim3 gridDim, dimensions of grid dim3 blockDim, dimensions of block uint3 blockIdx, block index within grid uint3 threadIdx, thread. However, the access pattern depends on how you are interpreting your data and also how you are accessing them by 1D, 2D and 3D blocks of threads.ĭim3 is an integer vector type based on uint3 that is used to specify dimensions. The memory is always a 1D continuous space of bytes. sizet dynamicShared: amount of additional shared memory to allocate when launching the kernel. The way you arrange the data in memory is independently on how you would configure the threads of your kernel. dim3 blockDim: 3D-block dimensions specifying the number of threads in each block. ![]()
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