使用CUDA实现Kmeans++的并行化
Parallelization of Kmeans++ using CUDA
摘要：
K-means++是一种改进K-means算法中初始种子搜索过程的算法。在该算法中，初始种子的选择是连续的概率，这是成比例的距离最近的中心。该算法最关键的问题是在串行模式下运行时，降低了聚类速度。在本文中，我们的目标是并行化的k-means++算法的最耗时的步骤。我们的目的是减少运行时间，同时保持串行算法的质量。
英文摘要：
K-means++ is an algorithm which is invented to improve the process of finding initial seeds in K-means algorithm. In this algorithm, initial seeds are chosen consecutively by a probability which is proportional to the distance to the nearest center. The most crucial problem of this algorithm is that when running in serial mode, it decreases the speed of clustering. In this paper, we aim to parallelize the most time consuming steps of the k-means++ algorithm. Our purpose is to reduce the running time while maintaining the quality of the serial algorithm.
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。
