Computer Architecture Workshop最新文献

{"title":"Data management requirements: The similarity of memory management, database systems, and message processing","authors":"O. Bray","doi":"10.1145/800180.810254","DOIUrl":"https://doi.org/10.1145/800180.810254","url":null,"abstract":"Memory management, database management, and message processing have in the past been defined in a relatively narrow way. With memory management the problem was to obtain cost effective use of real memory. Given a multiprogrammed environment, virtual memory systems allowed more effective use of expensive real memory. Memory management has become even more important with the development of very large and complex memory hierarchies. Database management systems were developed to allow the more effective use, sharing, and control of data resources - objectives which operating systems had previously provided for hardware resources. The driving force behind message processing has been the increased use of data communications and computer networks. This paper will consider the basis of the overlap in these areas, their common data management functions. Data management, as defined in this paper, includes the locating, routing, moving, and translating of data resources and the locating, reserving, and releasing of physical resources, i.e., primary and secondary storage.\u0000 The analysis performed in this paper is essential because of trends in computer architecture discussed below. Early hardware was designed for general purpose environments with software used to tailor it to specific applications. However, according to Gagliardi9 future systems will consist of a set of subsystems, including a storage subsystem at the core surrounded by computational, spooling, and communications subsystems. The computational subsystem is the traditional “number cruncher” part of the system. The spooling subsystem provides the I/O interface between the system and the outside world. The communications subsystem links the various subsystems together and provides an interface to the rest of the network if the system is part of a larger distributed system. The storage subsystem consists of all the system's storage resources and their control processes. It controls all levels of the system memory and storage hierarchy. The storage subsystem controls the allocation of the physical storage resources and the movement of the data resources through the system. Depending on how these resources are used, they may be non-conserved or conserved, and if conserved, either serially reusable or sharable. Physical and data resources may be located, and if necessary reserved, independently or jointly.","PeriodicalId":328859,"journal":{"name":"Computer Architecture Workshop","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122411520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associative/parallel processors for searching very large textual data bases","authors":"R. M. Bird, J. Tu, R. Worthy","doi":"10.1145/800180.810247","DOIUrl":"https://doi.org/10.1145/800180.810247","url":null,"abstract":"This paper describes an approach to solving a major problem in the information processing sciences— that of searching very large (5-50 billion characters) data bases of unstructured free-text for random queries within a reasonable time and at an affordable price.\u0000 The need by information specialists and knowledge workers for large, fast low-cost text and document retrieval systems is growing rapidly. Conventional approaches to the problem have usually depended upon expensive, general purpose computers, upon special pre-preprocessing of the textual data (e.g. file inverting, indexing, abstracting, etc.), and upon elaborate, costly software. The resulting retrieval systems often cost hundreds of dollars per query and the full scanning of an uninverted, unstructured billion byte textual data base could take hours of computer services. However, in spite of these restrictions, such full text search systems have proved useful and even indispensible for many applications.\u0000 Computer technology of the late 1960's and the 1970's, in both hardware and software (e.g., minicomputers, low-cost, high density disk storage, “chip” electronics, natural language query systems, etc.), have made i t practical to build special purpose, low-cost text retrieval systems. Such a system has been built, tested, and is now in a production stage. The system called the Associative File Processor (AFP), utilizes a conventional minicomputer (DEC's PDP-11/45) for control, off-the-shelf high density disks for storage, a special purpose parallel search module as a text term detector, and query and retrieval software. The AFP is currently being field tested at two sites. Full text, parallel searches on un-preprocessed textual data bases are being performed at the effective matching rates of 4 billion bytes per second (8K byte key memory times 500 Kbyte/second data stream). Estimated costs are 10 to 25 cents per query for a one billion byte data base. The costs per query and the time for searching increase in a linear fashion as data base increases. A basic architecture for the AFP is described and an implemented version is discussed. A more powerful term detector module is also under development. This system is designed around a finite state automaton algorithm.","PeriodicalId":328859,"journal":{"name":"Computer Architecture Workshop","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121095913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}