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科学通报  2014 

颗粒凝并动力学MonteCarlo方法的高效GPU并行计算

DOI: 10.1360/972013-76, PP. 1358-1368

Keywords: 颗粒群平衡模拟,凝并,随机模拟,并行计算,CUDA,计算效率

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Abstract:

MonteCarlo(MC)方法作为一种求解颗粒群平衡方程(PBE)的有效方法(PBMC),由于它对多维问题的适应性、符合实际颗粒动力学特征的离散和随机本质、程序结构相对简单、易于编程实现等优点受到人们持久、普遍的关注.但在涉及到颗粒凝并问题时,常规的PBMC方法计算代价较高,与模拟颗粒数目的平方成正比,限制了其工程应用.并行计算技术的快速发展,特别是近年来NVIDIA公司提出的计算统一设备架构(CUDA)为PBMC的快速高效模拟提供了一个良好的平台.本文在CUDA平台上实现了颗粒凝并动力学PBMC的图形处理器(GPU)并行计算(分别实现了累计概率法和接受-拒绝法选择凝并对)及中央处理器(CPU)的协同处理,与目前广泛运行于CPU的串行计算相比,取得了精确的计算结果和非常明显的加速,计算代价仅与颗粒数目成正比,在当前主流GPU/CPU设备上能够达到上百倍的加速比.

References

[1]  5 Zhao H, Kruis F E, Zheng C. Monte carlo simulation for aggregative mixing of nanoparticles in two-component systems. Ind Eng Chem Res, 2011, 50: 10652-10664
[2]  6 Kruis F E, Maisels A, Fissan H. Direct simulation Monte Carlo method for particle coagulation and aggregation. AIChE J, 2000, 46: 1735-1742
[3]  12 Zhao H, Zheng C. Correcting the multi-Monte Carlo method for particle coagulation. Powder Technol, 2009, 193: 120-123
[4]  13 Zhao H, Zheng C. A new event-driven constant-volume method for solution of the time evolution of particle size distribution. J Comput Phys, 2009, 228: 1412-1428
[5]  16 陈飞国, 葛蔚, 李静海. 复杂多相流动分子动力学模拟在GPU上的实现. 中国科学B辑: 化学, 2008, 38: 1120-1128
[6]  17 徐骥, 葛蔚, 任瑛, 等. Particle-Mesh Ewald(PME)算法的GPU加速. 计算物理, 2010, 27: 548-554
[7]  19 黄昌盛, 张文欢, 侯志敏, 等. 基于CUDA的格子Boltzmann方法: 算法设计与程序优化. 科学通报, 2011, 56: 2434-2444
[8]  20 Zhou H, Mo G, Wu F, et al. GPU implementation of lattice Boltzmann method for flows with curved boundaries. Comput Method Appl M, 2012, 225-228: 65-73
[9]  21 Xiong Q, Li B, Xu J, et al. Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units. Chin Sci Bull, 2012, 57: 707-715
[10]  22 Li C, Maa J Y, Kang H. Solving generalized lattice Boltzmann model for 3-D cavity flows using CUDA-GPU. Sci China Phys Mech Astron, 2012, 55: 1894-1904
[11]  23 王健, 许明, 葛蔚, 等. 单相流动数值模拟的SIMPLE算法在GPU上的实现. 科学通报, 2010, 55: 1979-1986
[12]  27 赵海波, 郑楚光. 描述颗粒凝并动力学的事件驱动常体积法. 中国科学E辑: 技术科学, 2008, 38: 1836-1849
[13]  28 Zhao H, Kruis F E, Zheng C. Reducing statistical noise and extending the size spectrum by applying weighted simulation particles in Monte Carlo simulation of coagulation. Aerosol Sci Tech, 2009, 43: 781-793
[14]  29 陶应龙, 王建国, 牛胜利, 等. MCATNP蒙特卡罗粒子输运程序的MPI并行化. 核电子学与探测技术, 2011, 31: 490-494
[15]  30 Matsumoto M, Nishimura T. Mersenne twister: A 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Trans Model Comput Simul, 1998, 8: 3-30
[16]  31 Vemury S, Pratsinis S E. Self-preserving size distributions of agglomerates. J Aerosol Sci, 1995, 26: 175-185
[17]  1 Friedlander S K. Smoke, Dust and Haze: Fundamentals of Aerosol Dynamics. New York: Oxford University Press, 2000
[18]  2 Seinfeld J H, Pandis S N. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. New York: Wiley-Interscience, 1997
[19]  3 Ramkrishna D. Population Balances: Theory and Applications to Particulate Systems in Engineering. San Diego: Academic Press, 2000
[20]  4 赵海波, 郑楚光. 离散系统动力学演变过程的颗粒群平衡模拟. 北京: 科学出版社, 2008
[21]  7 Matsoukas T, Lee K, Kim T. Mixing of components in two-component aggregation. AIChE J, 2006, 52: 3088-3099
[22]  8 Laurenzi I J, Bartels J D, Diamond S L. A general algorithm for exact simulation of multicomponent aggregation processes. J Comput Phys, 2002, 177: 418-449
[23]  9 Kraft M, Wagner W. An improved stochastic algorithm for temperature-dependent homogeneous gas phase reactions. J Comput Phys, 2003, 185: 139-157
[24]  10 Irizarry R. Fast Monte Carlo methodology for multivariate particulate systems-I: Point ensemble Monte Carlo. Chem Eng Sci, 2008, 63: 95-110
[25]  11 Zhao H, Kruis F E, Zheng C. Reducing statistical noise and extending the size spectrum by applying weighted simulation particles in monte carlo simulation of coagulation. Aerosol Sci Tech, 2009, 43: 781-793
[26]  14 Zhao H, Kruis F E, Zheng C. A differentially weighted Monte Carlo method for two-component coagulation. J Comput Phys, 2010, 229: 6931-6945
[27]  15 Zhao H, Zheng C. A population balance-Monte Carlo method for particle coagulation in spatially inhomogeneous systems. Comput Fluids, 2013, 71: 196-207
[28]  18 李博, 李曦鹏, 张云, 等. 耦合Nvidia/AMD两类GPU的格子玻尔兹曼模拟. 科学通报, 2009, 54: 3177-3184
[29]  24 董廷星, 李新亮, 李森, 等. GPU上计算流体力学的加速. 计算机系统应用, 2011, 20: 104-109
[30]  25 多相复杂系统国家重点实验室多尺度离散模拟项目组. 基于GPU的多尺度离散模拟并行计算. 北京: 科学出版社, 2009
[31]  26 Su C C, Smith M R, Kuo F A, et al. Large-scale simulations on multiple Graphics Processing Units (GPUs) for the direct simulation Monte Carlo method. J Comput Phys, 2012, 231: 7932-7958

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