Parallel backpropagation learning algorithms on CRAY Y-MP8/864 supercomputer

Shih-Lin Hung, H. Adeli*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

95 Scopus citations

Abstract

Parallel backpropagation neural networks learning algorithms have been developed employing the vectorization and microtasking capabilities of vector MIMD machines. They have been implemented in C on CRAY Y-MP/864 supercomputer under UNICOS operating system. The algorithms have been applied to two different domains: engineering design and image recognition, and their performance has been investigated. A maximum speedup of about 6.7 is achieved using eight processors for a large network with 5950 links due to microtasking only. When vectorization is combined with microtasking, a maximum speedup of about 33 is realized using eight processors.

Original languageEnglish
Pages (from-to)287-302
Number of pages16
JournalNeurocomputing
Volume5
Issue number6
DOIs
StatePublished - 1 Jan 1993

Keywords

  • Backpropagation
  • multitasking
  • neural networks
  • parallel processing
  • vectorization

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