神经网络在超立方体SIMD阵列上的高效实现

K. Kim, V.K.P. Kumar
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引用次数: 13

摘要

仅给出摘要形式,如下。提出了一种神经网络在超立方体SIMD阵列上的高效并行实现方法。作者展示了一个具有n个节点和e个连接的神经网络映射到具有(n+e)个处理元素的Hypercube数组上,这样通过预处理权矩阵,神经网络的每个更新步骤可以在8 log/sub 2/ (n+e)-3步中执行。该技术简单、高效,可应用于当前的并联机,如连接机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient implementation of neural networks on Hypercube SIMD arrays
Summary form only given, as follows. An efficient parallel implementation of neural networks on Hypercube SIMD arrays is presented. The authors show a mapping of a neural network having n nodes and e connections onto a Hypercube array having (n+e) processing elements such that each update step of the neural network can be performed in 8 log/sub 2/ (n+e)-3 steps by preprocessing the weight matrix. The technique is simple and efficient and can be used on current parallel machines such as the Connection Machine.<>
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