{"title":"Kohonen算法在计算机上的并行实现","authors":"R. Togneri, Y. Attikiouzel","doi":"10.1109/IJCNN.1991.170672","DOIUrl":null,"url":null,"abstract":"A parallel implementation of the Kohonen algorithm is proposed using partitioning of the network. This allows an exact implementation of the Kohonen algorithm as opposed to partitioning the data. By using a simple routing strategy the parallel Kohonen algorithm was tested on a PC-based transputer network without the need for any special distributed operating system. The execution time was measured for networks of different size and a varying number of transputers. The execution time decreased as the number of transputers increased. However, for comparatively small-size neural networks the communication overhead caused the execution time to increase when more transputers were used. Thus, the proposed parallel implementation of the Kohonen algorithm is not suitable for massively parallel architectures. It is concluded that in excess of 12 transputers can be used with network sizes of the order of 3000 neurons or more but no more than six transputers can be used with network sizes of the order of 120 neurons.<<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":"9","resultStr":"{\"title\":\"Parallel implementation of the Kohonen algorithm on transputer\",\"authors\":\"R. Togneri, Y. Attikiouzel\",\"doi\":\"10.1109/IJCNN.1991.170672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A parallel implementation of the Kohonen algorithm is proposed using partitioning of the network. This allows an exact implementation of the Kohonen algorithm as opposed to partitioning the data. By using a simple routing strategy the parallel Kohonen algorithm was tested on a PC-based transputer network without the need for any special distributed operating system. The execution time was measured for networks of different size and a varying number of transputers. The execution time decreased as the number of transputers increased. However, for comparatively small-size neural networks the communication overhead caused the execution time to increase when more transputers were used. Thus, the proposed parallel implementation of the Kohonen algorithm is not suitable for massively parallel architectures. It is concluded that in excess of 12 transputers can be used with network sizes of the order of 3000 neurons or more but no more than six transputers can be used with network sizes of the order of 120 neurons.<<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\":\"9\",\"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.1991.170672\",\"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.1991.170672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel implementation of the Kohonen algorithm on transputer
A parallel implementation of the Kohonen algorithm is proposed using partitioning of the network. This allows an exact implementation of the Kohonen algorithm as opposed to partitioning the data. By using a simple routing strategy the parallel Kohonen algorithm was tested on a PC-based transputer network without the need for any special distributed operating system. The execution time was measured for networks of different size and a varying number of transputers. The execution time decreased as the number of transputers increased. However, for comparatively small-size neural networks the communication overhead caused the execution time to increase when more transputers were used. Thus, the proposed parallel implementation of the Kohonen algorithm is not suitable for massively parallel architectures. It is concluded that in excess of 12 transputers can be used with network sizes of the order of 3000 neurons or more but no more than six transputers can be used with network sizes of the order of 120 neurons.<>
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