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PURPOSE The performance of all known Collapsed Cone Convolution/Superposition (CCCS) dose calculation methods on Graphics Processing Units (GPUs) is bounded by memory throughput. One major cause of this bottleneck is the traditional uniform grid representation of the density volume for human body, which generally contains many homogeneous areas. The common(More)
PURPOSE It is well-known that the performance of GPU-based Monte Carlo dose calculation implementations is bounded by memory bandwidth. One major cause of this bottleneck is the random memory writing patterns in dose deposition, which leads to several memory efficiency issues on GPU such as un-coalesced writing and atomic operations. We propose a new method(More)
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