环形多处理机上神经网络的并行处理

H. Midorikawa
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引用次数: 0

摘要

描述了一种在环形连接的分布式存储多处理机上具有反向传播学习过程的多层神经网络的高效并行仿真算法。每一层被划分为P个不相交的块,每个块被映射到P处理器系统的每个处理器上。利用该算法在一个环形连接的转发器系统上进行了并行仿真,分析了计算和通信的时间复杂度。结果表明,该算法可以在多处理器环连接的多处理器系统中提供较高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The parallel processing of neural networks on ring-shaped multiprocessor
An efficient parallel simulation algorithm is described for a multilayered neural network with a backpropagation learning procedure on a distributed-memory multiprocessor with ring connection. Each layer is divided into P disjoint blocks and each block is mapped on each processor of a P-processor system. The parallel simulation using this algorithm has been implemented on a system of transputers with ring connection, and the time complexity of both calculation and communication is analyzed. It is shown that the algorithm can provide high efficiency on a multiprocessor system which has a large number of processors connected in a ring.<>
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