{"title":"用于模式识别的微处理器阵列","authors":"S. M. Boxer, B. Batchelor","doi":"10.1049/IJ-CDT.1978.0018","DOIUrl":null,"url":null,"abstract":"A linear array of microprocessors provides a powerful computing system that is particularly well suited to many pattern-recognition and cluster-analysis algorithms. These often rely heavily upon the calculation of distances in high-dimensional vector spaces: distances can be computed at high speed by an array of identical processing elements, operating in parallel under the command of a central controller. To achieve high computing speeds in those pattern recognition algorithms which refer an input vector to each member of a set of stored reference vectors, the processing elements should each contain some `local? storage. Of course, not all pattern-recognition algorithms are parallel, and to accomodate these, the processing elements may be required to operate autonomously. Nevertheless, the system controller must, at all times, be able to force the entire array to operate under its control again. The array can operate in a third mode, namely acting as a pipe-line processor, which is useful in some situations (e.g. computing polynomials) and for transferring data between the array's local store and the system controller. A rectangular array is even faster than a linear one, but is, of course, more expensive. The cost and performance of an array of Intel 8080 microprocessors are compared to those of other systems.","PeriodicalId":344610,"journal":{"name":"Iee Journal on Computers and Digital Techniques","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1978-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Microprocessor arrays for pattern recognition\",\"authors\":\"S. M. Boxer, B. Batchelor\",\"doi\":\"10.1049/IJ-CDT.1978.0018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A linear array of microprocessors provides a powerful computing system that is particularly well suited to many pattern-recognition and cluster-analysis algorithms. These often rely heavily upon the calculation of distances in high-dimensional vector spaces: distances can be computed at high speed by an array of identical processing elements, operating in parallel under the command of a central controller. To achieve high computing speeds in those pattern recognition algorithms which refer an input vector to each member of a set of stored reference vectors, the processing elements should each contain some `local? storage. Of course, not all pattern-recognition algorithms are parallel, and to accomodate these, the processing elements may be required to operate autonomously. Nevertheless, the system controller must, at all times, be able to force the entire array to operate under its control again. The array can operate in a third mode, namely acting as a pipe-line processor, which is useful in some situations (e.g. computing polynomials) and for transferring data between the array's local store and the system controller. A rectangular array is even faster than a linear one, but is, of course, more expensive. The cost and performance of an array of Intel 8080 microprocessors are compared to those of other systems.\",\"PeriodicalId\":344610,\"journal\":{\"name\":\"Iee Journal on Computers and Digital Techniques\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1978-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iee Journal on Computers and Digital Techniques\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/IJ-CDT.1978.0018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iee Journal on Computers and Digital Techniques","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/IJ-CDT.1978.0018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A linear array of microprocessors provides a powerful computing system that is particularly well suited to many pattern-recognition and cluster-analysis algorithms. These often rely heavily upon the calculation of distances in high-dimensional vector spaces: distances can be computed at high speed by an array of identical processing elements, operating in parallel under the command of a central controller. To achieve high computing speeds in those pattern recognition algorithms which refer an input vector to each member of a set of stored reference vectors, the processing elements should each contain some `local? storage. Of course, not all pattern-recognition algorithms are parallel, and to accomodate these, the processing elements may be required to operate autonomously. Nevertheless, the system controller must, at all times, be able to force the entire array to operate under its control again. The array can operate in a third mode, namely acting as a pipe-line processor, which is useful in some situations (e.g. computing polynomials) and for transferring data between the array's local store and the system controller. A rectangular array is even faster than a linear one, but is, of course, more expensive. The cost and performance of an array of Intel 8080 microprocessors are compared to those of other systems.