标题： 基于多GPU的Swendsen-Wang多簇算法用于二维q状态Potts模型的模拟 显示英文标题

标题： Multi-GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional q-state Potts model

摘要： 我们介绍了使用通用统一设备架构（CUDA）的多GPU计算，用于二维（2D）q状态Potts模型的Swendsen-Wang多簇算法。 扩展我们针对单GPU计算的算法[Comp. Phys. Comm. 183 (2012) 1155]，我们实现了多GPU的Swendsen-Wang多簇算法的GPU计算。 我们将代码实现于大规模开放科学超级计算机TSUBAME 2.0，并测试了二维Potts模型模拟的性能和可扩展性。 使用256块Tesla M2050 GPU，在线性系统尺寸L=65536的临界温度下，得到q=2 Potts模型（Ising模型）的性能为每纳秒37.3次自旋翻转。 显示英文摘要

摘要： We present the multiple GPU computing with the common unified device architecture (CUDA) for the Swendsen-Wang multi-cluster algorithm of two-dimensional (2D) q-state Potts model. Extending our algorithm for single GPU computing [Comp. Phys. Comm. 183 (2012) 1155], we realize the GPU computation of the Swendsen-Wang multi-cluster algorithm for multiple GPUs. We implement our code on the large-scale open science supercomputer TSUBAME 2.0, and test the performance and the scalability of the simulation of the 2D Potts model. The performance on Tesla M2050 using 256 GPUs is obtained as 37.3 spin flips per a nano second for the q=2 Potts model (Ising model) at the critical temperature with the linear system size L=65536.