Kohonen算法在计算机上的并行实现

R. Togneri, Y. Attikiouzel
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引用次数: 9

摘要

提出了一种利用网络分区实现Kohonen算法的并行算法。这允许Kohonen算法的精确实现,而不是对数据进行分区。采用简单的路由策略,在不需要任何特殊的分布式操作系统的情况下,在基于pc的计算机网络上对并行Kohonen算法进行了测试。对不同大小和不同数量的转发器网络的执行时间进行了测量。执行时间随着转发器数量的增加而减少。然而,对于相对较小的神经网络,当使用更多的转发器时,通信开销导致执行时间增加。因此,提出的Kohonen算法的并行实现不适合大规模并行架构。结果表明,在3000神经元量级的网络中,可以使用超过12个的转发器,而在120神经元量级的网络中,可以使用不超过6个的转发器。
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Parallel implementation of the Kohonen algorithm on transputer
A parallel implementation of the Kohonen algorithm is proposed using partitioning of the network. This allows an exact implementation of the Kohonen algorithm as opposed to partitioning the data. By using a simple routing strategy the parallel Kohonen algorithm was tested on a PC-based transputer network without the need for any special distributed operating system. The execution time was measured for networks of different size and a varying number of transputers. The execution time decreased as the number of transputers increased. However, for comparatively small-size neural networks the communication overhead caused the execution time to increase when more transputers were used. Thus, the proposed parallel implementation of the Kohonen algorithm is not suitable for massively parallel architectures. It is concluded that in excess of 12 transputers can be used with network sizes of the order of 3000 neurons or more but no more than six transputers can be used with network sizes of the order of 120 neurons.<>
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