大规模并行实现的反向传播算法的容错性和学习性能

[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation Pub Date : 1990-10-08 DOI:10.1109/FMPC.1990.89483

P. Murali, H. Wechsler, M. Manohar

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引用次数: 4

摘要

将反向传播(BP)算法映射到SIMD(单指令流，多数据流)机器上，例如大规模并行处理器。结果表明，基于BP的连接网络的规模可以扩大到更大的规模，从而提高了性能。具体来说，可以提高容错性和学习速度。

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Fault-tolerance and learning performance of the back-propagation algorithm using massively parallel implementation

Mapping the backpropagation (BP) algorithm onto an SIMD (single-instruction-stream, multiple-data-stream) machine, such as the Massively Parallel Processor, is considered. It is shown that the size of the connectionist network underlying BP can be scaled up to large sizes, resulting in improved performance. Specifically, both fault tolerance and learning speed can be enhanced.<>

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[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation

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