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Domain decomposition based on spatial locality is a classical data-parallel problem whose solution may improve by orders of magnitude when implemented on a GPU. Among the data structures involved in domain decomposition, uniform grids are widely used to speed up simulations in a number of fields, including computational physics and graphics. In this work, we present two commonly used approaches to generate uniform grids on GPUs and propose a new single-pass method that has several advantages over the previous ones. We also present some performance results of our CUDA implementation of a broad-phase collision detection algorithm for particles simulation, comparing the different methods. In some tests our method achieves a speedup of 2 compared to the fastest known method supporting a fixed maximum number of elements per cell, and a speedup of 7 compared with the fastest method without such a constraint.
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