{"title":"sdn -3:在严格数字神经网络组合优化中用于O(1)并行处理的简单处理器结构","authors":"T. Nakagawa, H. Kitagawa, E. Page, G. Tagliarini","doi":"10.1109/IJCNN.1991.170755","DOIUrl":null,"url":null,"abstract":"An architecture for high-speed and low-cost processors based upon SDNNs, (strictly digital neural networks) to solve combinatorial optimization problems within O(1) time is presented. Combinatorial optimization problems were programmed as a set selection problem with the k-out-of-n design rule, and solved by a cluster of SDN elementary processors in a discrete operation manner of TOH (traveling on hypercube), which is a rule for synchronized parallel execution. In all simulation cases, the latest SDNN-3 hardware achieved O(1) parallel processing in solving large-scale N-queen problems of up to 1200-queens. It was confirmed that all of the solutions are optimum, and that the SDNN processor always converges to global minima without any external one.<<ETX>>","PeriodicalId":211135,"journal":{"name":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"SDNN-3: A simple processor architecture for O(1) parallel processing in combinatorial optimization with strictly digital neural networks\",\"authors\":\"T. Nakagawa, H. Kitagawa, E. Page, G. Tagliarini\",\"doi\":\"10.1109/IJCNN.1991.170755\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An architecture for high-speed and low-cost processors based upon SDNNs, (strictly digital neural networks) to solve combinatorial optimization problems within O(1) time is presented. Combinatorial optimization problems were programmed as a set selection problem with the k-out-of-n design rule, and solved by a cluster of SDN elementary processors in a discrete operation manner of TOH (traveling on hypercube), which is a rule for synchronized parallel execution. In all simulation cases, the latest SDNN-3 hardware achieved O(1) parallel processing in solving large-scale N-queen problems of up to 1200-queens. It was confirmed that all of the solutions are optimum, and that the SDNN processor always converges to global minima without any external one.<<ETX>>\",\"PeriodicalId\":211135,\"journal\":{\"name\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1991.170755\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1991.170755","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SDNN-3: A simple processor architecture for O(1) parallel processing in combinatorial optimization with strictly digital neural networks
An architecture for high-speed and low-cost processors based upon SDNNs, (strictly digital neural networks) to solve combinatorial optimization problems within O(1) time is presented. Combinatorial optimization problems were programmed as a set selection problem with the k-out-of-n design rule, and solved by a cluster of SDN elementary processors in a discrete operation manner of TOH (traveling on hypercube), which is a rule for synchronized parallel execution. In all simulation cases, the latest SDNN-3 hardware achieved O(1) parallel processing in solving large-scale N-queen problems of up to 1200-queens. It was confirmed that all of the solutions are optimum, and that the SDNN processor always converges to global minima without any external one.<>
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