基于程序定义及动态进程的PVM与MPI比较

MPI（Message Passing Interface）与PVM（Parallel Virtual Machine）均为分布式计算中广泛应用的两种并行计算环境。PVM出现的时间早于MPI,且它是一个自包含系统,而MPI是一个标准。目前,在PVM与MPI互相靠拢的过程中,关于两者的比较越来越多。其目的便是通过比较,结合二者之优点,发展起性能更加强大的并行计算环境。仅从程序的定义与实现、以及动态进程两个方面简单阐述了两者的不同,事实上,二者通常被用于解决不同的问题。     

Parallel Distributed Implementation of Truss Optimization on a Local Area Network

A two-level optimization method for the design of complex truss and parallel distributed implementation on a LAN is presented using parallel virtual machine (PVM) for Win 32 as message passing between PCs. The volumes of truss are minimized by decomposing the original optimization problem into a number of bar optimization problems executed concurrently and a coordinate optimization problem, subject to constraints on nodal displacements, and stresses, buckling and crippling of bars, etc. The system sensitivity analysis that derives the partial derivatives of displacements and stresses with respect to areas are also performed in parallel so as to shorten the analysis time. The convergence and the speedup performances as well as parallel computing efficiency of the method are investigated by the optimization examples of a 52-bar planar truss and a 3 126-bar three-diraensional truss. The results show that the ideal speedup is obtained in the cases of 2 PCs for the 3 126-bar space truss optimization, while no speedup is observed for the 52-bar truss. It is concluded that (1) the parallel distributed algorithm proposed is efficient on the PC-based LAN for the coarsegrained large optimization problem; (2) to get a high speedup, the problem granularity should match with the network granularity;and (3) the larger the problem size is, the higher the parallel efficiency is.     

基于机群的并行BP算法的设计与实现

首先说明了一般的BP算法无法满足实时运算的要求，然后根据机群环境的特点，提出了按训练样本集的均衡分配对该算法实施并行化，实测数据表明在大样本集的情况下，此并行算法的效果明显。