A parallel formulation of back-propagation learning on distributed memory multiprocessors
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This paper presents a mapping scheme for parallel pipelined execution of the Back-propagation Learning Algorithm on distributed memory multiprocessors. The proposed implementation exhibits inter-layer or pipelined parallelism, unique to the multilayer neural networks. Simple algorithms have been presented, which allow the data transfer involved in both recall and learning phases of the back-propagation algorithm to be carried out with a small communication overhead. The effectiveness of the mapping scheme has been illustrated, by estimating the speedup of the proposed implementation on an array of T-805 transputers.
author list (cited authors)
Mahapatra, S., Mahapatra, R. N., & Chatterji, B. N.
complete list of authors
Mahapatra, S||Mahapatra, RN||Chatterji, BN