【摘要】：基于密度峰值的聚類方法 DP(density peak)由于其新穎有效的特點(diǎn)而廣泛應(yīng)用于科學(xué)研究。然而,當(dāng)確定集群中心時(shí),DP會(huì)對(duì)每對(duì)數(shù)據(jù)點(diǎn)操作多次,從而導(dǎo)致較高的計(jì)算復(fù)雜度。在本文中,我們提出了一種基于GPU(graphics processing unit)的高效并行密度峰值算法。我們分析密度峰值聚類算法的原理來(lái)研究其計(jì)算瓶頸,并評(píng)估其并行的潛力。根據(jù)分析,我們提出了CUDA-DP(compute unified device architecture-DP),一種針對(duì)GPU架構(gòu)的高效并行密度峰值聚類算法,并用CUDA實(shí)現(xiàn)了這種并行方法。具體來(lái)說(shuō),我們使用共享內(nèi)存減少了全局內(nèi)存訪問(wèn)量。更進(jìn)一步,為了利用GPU的合并訪問(wèn)機(jī)制,我們將CUDA-DP程序的數(shù)據(jù)結(jié)構(gòu)從AOS(array of structures)重構(gòu)為SOA(structure of arrays)。另外,我們分別引入二進(jìn)制搜索方法和采樣方法,以避免對(duì)距離矩陣進(jìn)行排序造成的計(jì)算開(kāi)銷。實(shí)驗(yàn)結(jié)果表明,與基于CPU的密度峰值實(shí)現(xiàn)相比,CUDA-DP可以實(shí)現(xiàn)超過(guò)45倍的加速。
[Abstract]:DP (density peak), a clustering method based on peak density, is widely used in scientific research because of its novel and effective characteristics. However, when the cluster center is determined, DP operates on each pair of data points multiple times, resulting in high computational complexity. In this paper, we propose an efficient parallel peak density algorithm based on GPU (graphics processing unit). We analyze the principle of peak density clustering algorithm to study its computational bottleneck and evaluate its parallelism potential. According to the analysis, we propose CUDA-DP (compute unified device architecture-DP), an efficient parallel density peak clustering algorithm for GPU architecture, and implement this parallel method with CUDA. Specifically, we use shared memory to reduce global memory access. Further, in order to take advantage of GPU's merge access mechanism, we reconstruct the data structure of CUDA-DP programs from AOS (array of structures) to SOA (structure of arrays). In addition, the binary search method and the sampling method are introduced to avoid the computational overhead caused by sorting the distance matrix. The experimental results show that CUDA-DP can achieve more than 45 times acceleration compared with the density peak realization based on CPU.
【作者單位】： National
【基金】：supported by the National Basic Research Program(973)of China(No.2014CB340303) the National Natural Science Foundation of China(Nos.61502509 and 61222205) the Program for New Century Excellent Talents in University the Fok Ying-Tong Education Foundation(No.141066)
【分類號(hào)】：TP311.13

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本文編號(hào)：2271690