GPU上的八叉树方法
Oct-tree Method on GPU
摘要：
kd树是计算机科学中的一个基本工具。其中，kd树搜索（八叉树方法）的应用，以快速评估粒子的相互作用和邻居搜索是非常重要的，因为这些问题的计算复杂度从O（N^2）与暴力方法减少到O（N log N）与树的方法，其中N是粒子的数量。在本文中，我们提出了一个并行实现的树的方法在图形处理器单元（GPU）上运行。我们成功地运行了一个非常有效的宇宙结构形成模拟。在我们的系统上，花费大约900美元，使用N~2.87x10^6个粒子运行了5.79小时，总共执行了1.2x10^13个力评估。我们获得了21.8 Gflops的持续计算速度和41.6 Gflops/Gflops的成本，比2006年的记录高出2.5倍。
英文摘要：
The kd-tree is a fundamental tool in computer science. Among others, an application of the kd-tree search (oct-tree method) to fast evaluation of particle interactions and neighbor search is highly important since computational complexity of these problems are reduced from O(N^2) with a brute force method to O(N log N) with the tree method where N is a number of particles. In this paper, we present a parallel implementation of the tree method running on a graphic processor unit (GPU). We successfully run a simulation of structure formation in the universe very efficiently. On our system, which costs roughly $900, the run with N ~ 2.87x10^6 particles took 5.79 hours and executed 1.2x10^13 force evaluations in total. We obtained the sustained computing speed of 21.8 Gflops and the cost per Gflops of 41.6/Gflops that is two and half times better than the previous record in 2006.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
