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Efficient space virtualization for the Hoshen-Kopelman algorithm

机译:Hoshen-Kopelman算法的高效空间虚拟化

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In this paper, the efficient space virtualisation for the Hoshen-Kopelman algorithm is presented. We observe minimal parallel overhead during computations, due to negligible communication costs. The proposed algorithm is applied for computation of random-site percolation thresholds for four dimensional simple cubic lattice with sites' neighborhoods containing next-next-nearest neighbors (3NN). The obtained percolation thresholds are p(C)(NN) = 0.19680(23), p(C)(2NN) =0.08410(23), p(C)(3NN)=0.04540(23), p(C)(2NN+NN)=0.06180(23), p(C)(3NN+NN) = 0.04000(23), p(C)(3NN + 2NN) = 0.03310(23), p(C)(3NN + 2NN + NN) = 0.03190(23), where 2NN and NN stand for next-nearest neighbors and nearest neighbors, respectively.
机译:本文介绍了Hoshen-Kopelman算法的有效空间虚拟化。 由于沟通成本可忽略不计,我们在计算期间观察到最小的平行开销。 所提出的算法用于计算四维简单立方格的随机站点渗透阈值与包含下一个最近邻居(3nn)的站点的邻域的四维简单立方格阈值。 得到的渗透阈值是p(c)(nn)= 0.19680(23),p(c)(2nn)= 0.08410(23),p(c)(3nn)= 0.04540(23),p(c)(2nn + NN)= 0.06180(23),P(C)(3NN + NN)= 0.04000(23),P(C)(3NN + 2NN)= 0.03310(23),P(C)(3nn + 2nn + Nn) = 0.03190(23),其中分别为下一个最近的邻居和最近邻居2nn和nn。

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