arXiv 1208.36582012-08astro-ph.IMastro-ph.CO

GPU的宇宙学计算

Cosmological Calculations on the GPU

Deborah Bard, Matthew Bellis, Mark T. Allen, Hasmik Yepremyan, Jan M. Kratochvil

备注：: 10 pages, 1 figure; accepted by Astronomy and Computing; code available at https://github.com/djbard/ccogs

摘要：

宇宙学测量需要在大型数据集上计算非平凡量。下一代巡天望远镜（如DES、PanSTARRS和LSST）将测量数十亿个星系。这些数据集的规模和所涉及的计算的性质使宇宙学计算成为在图形处理单元（GPU）上实现的理想模型。我们考虑两个宇宙学计算，两点角关联函数和孔径质量统计，并旨在提高计算时间，通过构建代码计算它们的GPU上。使用CUDA，我们在GPU上实现了这两种算法，并将计算速度与CPU上运行的可比代码进行了比较。与在CPU上执行相同的计算相比，我们获得了10 - 180倍的代码加速。该守则已公开提供。

英文摘要：

Cosmological measurements require the calculation of nontrivial quantities over large datasets. The next generation of survey telescopes (such as DES, PanSTARRS, and LSST) will yield measurements of billions of galaxies. The scale of these datasets, and the nature of the calculations involved, make cosmological calculations ideal models for implementation on graphics processing units (GPUs). We consider two cosmological calculations, the two-point angular correlation function and the aperture mass statistic, and aim to improve the calculation time by constructing code for calculating them on the GPU. Using CUDA, we implement the two algorithms on the GPU and compare the calculation speeds to comparable code run on the CPU. We obtain a code speed-up of between 10 - 180x faster, compared to performing the same calculation on the CPU. The code has been made publicly available.

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