Parallel sampling in Bayesian networks

V. Rego, A. Schulz
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Abstract

An easily parallelized version of the Pearl sequential algorithm is presented, along with experimental results utilizing an Ncube/1, hypercube and a Sequent shared memory multiprocessor. Pearl's concurrent simulation algorithm is briefly reviewed, and three modifications to this algorithm are proposed. These modifications, known as stack, phase, and parallel simulations, show considerable speedup in experiments performed on the hypercube.<>
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贝叶斯网络中的并行抽样
本文提出了一种易于并行化的Pearl序列算法,并给出了利用Ncube/1、hypercube和sequential共享内存多处理器的实验结果。简要回顾了Pearl并行仿真算法,并对该算法进行了三种改进。这些修改被称为堆栈、相位和并行模拟,在超立方体上进行的实验中显示出相当大的加速。
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