Title :
Pore Network Simulation via Monte Carlo Algorithms on GPUs
Author :
Matadamas, Jorge ; Roman, Graciela ; Rojas, FeÌlix ; Castro, Miguel A. ; Cordero, Salomon S. ; Aguilar, Mario
Author_Institution :
Dept. de Ing. Electr., Univ. Autonoma Metropolitana, Mexico City, Mexico
Abstract :
Sequential Monte Carlo simulation of pore networks, according to the Dual Site-Bond Model (DSBM) has been used successfully in the study of the structure and properties of porous media; these studies have a variety of applications (e.g. enhanced oil recovery, expedient gas storage, faster catalytic reactions, etc.) In the simplest form of DSBM, each pore is classified as a site or as a bond; the sites are modeled as hollow spheres and the bonds like hollow cylinders; each bond interconnects two sites providing the fulfillment of the construction principle (CP), which indicates that the size of a bond should always be smaller or at most equal to the sizes of each one of its two interconnected sites. The complexity of the simulation lies on making all pores of a 3D network to respect the CP. Previous work includes pore network simulation performed through a Monte Carlo parallel algorithm, by using a multi-core node cluster with C+MPI. Since the graphic processing unit (GPU) architecture is now an efficient alternative to parallel computing, in this work we propose three parallel Monte Carlo algorithms for pore network simulation employing CUDA and CUDA+MPI. First we propose two different data partitioning using a GPU, planes-CUDA and cubes-CUDA. Then, we propose a version of planes-CUDA that uses three interconnected GPUs. Our results show that the cubes-CUDA algorithm using a GPU attains better performance than the others.
Keywords :
Monte Carlo methods; graphics processing units; materials science computing; parallel algorithms; parallel architectures; porous materials; 3D network; CUDA+MPI; DSBM; GPU; bond size; construction principle; cubes-CUDA; data partitioning; dual site-bond model; graphic processing unit architecture; parallel Monte Carlo algorithms; planes-CUDA; pore network simulation; porous media properties; porous media structure; sequential Monte Carlo simulation; Computational modeling; Graphics processing units; Hardware; Instruction sets; Kernel; Monte Carlo methods; Three-dimensional displays; CUDA; GPU cluster; MPI; Parallel Monte Carlo Method; Pore network simulation;
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
DOI :
10.1109/TLA.2014.6827878