Neural network simulations on massively parallel computers: Applications in chemical physics

Bobby G. Sumpter, Raymond E. Guenther, Christian Halloy, Coral Getino, Donald W. Noid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A fully connected feedforward neural network is simulated on a number of parallel computers (MasPar-1, Connection Machine CM5, Intel iPSC-2 and iPSC-860) and the performance is compared to that obtained on sequential vector computers (Cray YMP, Cray C90, IBM-3090) and to a scaler workstation (IBM RISC-6000). Peak performances of up to 342 million connections per second (MCPS) could be obtained on the Cray C90 using a single processor while the optimum performance obtained on the parallel computers was 90 MCPS using 4096 processors. Efficiency such as these has enabled neural network computations to be carried out for a number of chemical physics problems. Several examples are discussed: multi-dimensional function/surface fitting, coordinate transformations, and predictions of physical properties from chemical structure.

Original languageEnglish
Title of host publicationNew Trends in Neural Computation - International Workshop on Artificial Neural Networks, IWANN 1993, Proceedings
EditorsJose Mira, Joan Cabestany, Alberto Prieto
PublisherSpringer Verlag
Pages454-458
Number of pages5
ISBN (Print)9783540567981
DOIs
StatePublished - 1993
EventInternational Workshop on Artificial Neural Networks, IWANN 1993 - Sitges, Spain
Duration: Jun 9 1993Jun 11 1993

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume686
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshop on Artificial Neural Networks, IWANN 1993
Country/TerritorySpain
CitySitges
Period06/9/9306/11/93

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