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- W2742476360 abstract "Our study focuses on accelerating the computation of Zernike moments on graphics processing units (GPUs). There are two ideas to achieve the goal. First is to implement a novel re-layout that involves reordering the image pixels and addressing the diagonal pixels in advance, so that computations of all pixels are allocated to an octant effectively. Second is to the leverage the constant memory to store precomputed values used across GPU threads. An in-depth study has been carried out to evaluate the performance in each case and to compare against GPU implementation of other algorithms and to discuss the bottleneck. The result shows that our approach is effective and achieves significant performance improvement compared to other GPU state-of-the-art implementations. Furthermore, our approach is suited for allocating the data flow into multiple GPUs." @default.
- W2742476360 created "2017-08-17" @default.
- W2742476360 creator A5056466890 @default.
- W2742476360 creator A5083483046 @default.
- W2742476360 creator A5084408832 @default.
- W2742476360 date "2018-01-01" @default.
- W2742476360 modified "2023-10-15" @default.
- W2742476360 title "Efficient optimization approach for fast GPU computation of Zernike moments" @default.
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- W2742476360 doi "https://doi.org/10.1016/j.jpdc.2017.07.008" @default.
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