Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index ...Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.展开更多
Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more ...Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more used in the milling modeling areas. But simulative efficiency is decreasin g with increase of its complexity. As a result, application of the method is lim ited. Aimed at above question, high-efficient algorithm for milling process sim ulation is studied. It is important for milling process simulation’s applicatio n. Parallel computing is widely used to solve the large-scale computation question s. Its advantages include system flexibility, robust, high-efficient computing capability and high ratio of performance to price. With the development of compu ter network, utilizing the computing resource in the Internet, a virtual computi ng environment with powerful computing capability can be consisted by microc omputers, and the difficulty of building hardware environment which is used to s upport parallel computing is reduced. How to use network technology and parallel algorithm to improve simulative effic iency for milling forces simulation is investigated in the paper. In order to pr edict milling forces, a simplified local milling forces model is used in the pap er. End milling cutter is assumed to be divided by r number of differential elem ents along the axial direction of the cutter. For a given time, the total cuttin g forces can be obtained by summarizing the resultant cutting force produced by each differential cutter disc. Divide the whole simulative time into some segmen ts, send these program’s segments to microcomputers in the Internet and obtain the result of the program’s segments, all of the result of program’s segments a re composed the final result. For implementing the algorithm, a distributed Parallel computing framework is de signed in the paper. In the framework, web server plays a role of controller. Us ing Java RMI(remote method interface), the computing processes in computing serv er are called by web server. There are lots of control processes in web server a nd control the computing servers. The codes of simulative algorithm can be dynam ic sent to the computing servers, and milling forces at the different time are c omputed through utilizing the local computer’s resource. The results that are ca lculated by every computing servers are sent to the web server, and composed the final result. The framework can be used by different simulative algorithm. Comp ared with the algorithm running single machine, the efficiency of provided algor ithm is higher than that of single machine.展开更多
针对具有物理机制的分布式水文模型对大流域、长序列模拟计算时间长、模拟速度慢的问题,引入基于GPU的并行计算技术,实现分布式水文模型WEP-L(water and energy transfer processes in large river basins)产流过程的并行化。选择鄱阳...针对具有物理机制的分布式水文模型对大流域、长序列模拟计算时间长、模拟速度慢的问题,引入基于GPU的并行计算技术,实现分布式水文模型WEP-L(water and energy transfer processes in large river basins)产流过程的并行化。选择鄱阳湖流域为实验区,采用计算能力为8.6的NVIDIA RTX A4000对算法性能进行测试。研究表明:提出的基于GPU的分布式水文模型并行算法具有良好的加速效果,当线程总数越接近划分的子流域个数(计算任务量)时,并行性能越好,在实验流域WEP-L模型子流域单元为8712个时,加速比最大达到2.5左右;随着计算任务量的增加,加速比逐渐增大,当实验流域WEP-L模型子流域单元增加到24897个时,加速比能达到3.5,表明GPU并行算法在大尺度流域分布式水文模型计算中具有良好的发展潜力。展开更多
基金Project(61273187)supported by the National Natural Science Foundation of ChinaProject(61321003)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China
文摘Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.
文摘Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more used in the milling modeling areas. But simulative efficiency is decreasin g with increase of its complexity. As a result, application of the method is lim ited. Aimed at above question, high-efficient algorithm for milling process sim ulation is studied. It is important for milling process simulation’s applicatio n. Parallel computing is widely used to solve the large-scale computation question s. Its advantages include system flexibility, robust, high-efficient computing capability and high ratio of performance to price. With the development of compu ter network, utilizing the computing resource in the Internet, a virtual computi ng environment with powerful computing capability can be consisted by microc omputers, and the difficulty of building hardware environment which is used to s upport parallel computing is reduced. How to use network technology and parallel algorithm to improve simulative effic iency for milling forces simulation is investigated in the paper. In order to pr edict milling forces, a simplified local milling forces model is used in the pap er. End milling cutter is assumed to be divided by r number of differential elem ents along the axial direction of the cutter. For a given time, the total cuttin g forces can be obtained by summarizing the resultant cutting force produced by each differential cutter disc. Divide the whole simulative time into some segmen ts, send these program’s segments to microcomputers in the Internet and obtain the result of the program’s segments, all of the result of program’s segments a re composed the final result. For implementing the algorithm, a distributed Parallel computing framework is de signed in the paper. In the framework, web server plays a role of controller. Us ing Java RMI(remote method interface), the computing processes in computing serv er are called by web server. There are lots of control processes in web server a nd control the computing servers. The codes of simulative algorithm can be dynam ic sent to the computing servers, and milling forces at the different time are c omputed through utilizing the local computer’s resource. The results that are ca lculated by every computing servers are sent to the web server, and composed the final result. The framework can be used by different simulative algorithm. Comp ared with the algorithm running single machine, the efficiency of provided algor ithm is higher than that of single machine.
文摘针对具有物理机制的分布式水文模型对大流域、长序列模拟计算时间长、模拟速度慢的问题,引入基于GPU的并行计算技术,实现分布式水文模型WEP-L(water and energy transfer processes in large river basins)产流过程的并行化。选择鄱阳湖流域为实验区,采用计算能力为8.6的NVIDIA RTX A4000对算法性能进行测试。研究表明:提出的基于GPU的分布式水文模型并行算法具有良好的加速效果,当线程总数越接近划分的子流域个数(计算任务量)时,并行性能越好,在实验流域WEP-L模型子流域单元为8712个时,加速比最大达到2.5左右;随着计算任务量的增加,加速比逐渐增大,当实验流域WEP-L模型子流域单元增加到24897个时,加速比能达到3.5,表明GPU并行算法在大尺度流域分布式水文模型计算中具有良好的发展潜力。
