Mapping Of Backpropagation Learning Onto Distributed Memory Multiprocessors

This paper presents a mapping scheme for p a d e l pipelined execution of the Backpropagation Learning Algorithm o n dtktributed memory multiprocessors (DMMs). The proposed implementation ezhibits training set parallelism that involves batch updating. Simple algorithms have been presented, which allow the data transfer involved in both forward and backward execution3 phases of the backpropagation algorithm t o be carried out with a small communication overhead. The egectiveness of our mapping has been illustrated, by estimating the speedup of a proposed implementation on an away of T-805 transputers.