T. Saito, Y. Baba, K. Nakagawa, Y. Fuwa, Y. Shimokawa
{"title":"A MULTINEURO computer system by using high performance digital neuro processor","authors":"T. Saito, Y. Baba, K. Nakagawa, Y. Fuwa, Y. Shimokawa","doi":"10.1109/SICE.1995.526722","DOIUrl":null,"url":null,"abstract":"We have developed an accelerator device \"MULTINEURO-A\" which incorporates multiple processors (one master node and plural slave nodes) dedicated to neural network high-speed computing realized on an engineering workstation. Nodes are connected by two data paths, broadcast bus and ring bus. Processing speed is in proportion to the number of processors. It is built in two boards (master and slave) having 64 VLSI processors that offers to 1.5 billion connections per seconds. It processes forward/backward calculation of multilayer perceptron type neural networks, feedback type neural networks such as Hopfield model, and any other types by programming for parallel processing.","PeriodicalId":344374,"journal":{"name":"SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SICE.1995.526722","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We have developed an accelerator device "MULTINEURO-A" which incorporates multiple processors (one master node and plural slave nodes) dedicated to neural network high-speed computing realized on an engineering workstation. Nodes are connected by two data paths, broadcast bus and ring bus. Processing speed is in proportion to the number of processors. It is built in two boards (master and slave) having 64 VLSI processors that offers to 1.5 billion connections per seconds. It processes forward/backward calculation of multilayer perceptron type neural networks, feedback type neural networks such as Hopfield model, and any other types by programming for parallel processing.
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