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    <p>One way to solve this problem is imaging the cube as a set of Z slides. The coordinates X, Y refers to the width and height of the image, and the Z coordinate to each slide in the Z dimension. Each thread will iterate in the Z coordinate to accumulate the values.</p> <p>With this in mind, configure a kernel to launch a block of 16x16 threads and a grid of enough blocks to process the width and height of the image (I'm assuming a gray scale image with 1 byte per pixel):</p> <pre><code>#define THREADS 16 // kernel configuration dim3 dimBlock = dim3 ( THREADS, THREADS, 1 ); dim3 dimGrid = dim3 ( WIDTH / THREADS, HEIGHT / THREADS ); // call the kernel kernel&lt;&lt;&lt;dimGrid, dimBlock&gt;&gt;&gt;(i_data, o_Data, WIDTH, HEIGHT, DEPTH); </code></pre> <p>If you are clear how to index a 2D array, loop through the Z dimension would be also clear</p> <pre><code>__global__ void kernel(unsigned char* i_data, unsigned char* o_data, int WIDTH, int HEIGHT, int DEPTH) { // in your kernel map from threadIdx/BlockIdx to pixel position int x = threadIdx.x + blockIdx.x * blockDim.x; int y = threadIdx.y + blockIdx.y * blockDim.y; // calculate the global index of a pixel into the image array // this global index is to the first slide of the cube int idx = x + y * WIDTH; // partial results int r = 0; // iterate in the Z dimension for (int z = 0; z &lt; DEPTH; ++z) { // WIDTH * HEIGHT is the offset of one slide int idx_z = z * WIDTH*HEIGHT + idx; r += i_data[ idx_z ]; } // o_data is a 2D array, so you can use the global index idx o_data[ idx ] = r; } </code></pre> <p>This is a naive implementation. In order to maximize memory throughput, the data should be properly aligned. </p>
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    1. COThanks! I think I was way over thinking the problem and making the indexing overly complicated in my mind. Right now, the naive implementation is all I need as this is just a quick test initialization of some stuff...not what our final program is doing.
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    2. CO@HillaryD Good. Do not forget mark a valid answer if you think It is useful.
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