• DocumentCode
    3267451
  • Title

    Assessing document relevance with run-time reconfigurable machines

  • Author

    Gunther, Bernard ; Milne, George ; Narasimhan, Lakshmi

  • Author_Institution
    Sch. of Comput. & Inf. Sci., Univ. of South Australia, The Levels, SA, Australia
  • fYear
    1996
  • fDate
    17-19 Apr 1996
  • Firstpage
    10
  • Lastpage
    17
  • Abstract
    Free text database searching is a natural candidate for acceleration by run time reconfigurable custom computing machines. We describe a fully pipelined search machine architecture for scoring the relevance of textual documents against approximately 100 relevant target words, with provision for limited regular expression matching and error tolerance. An implementation on the SPACE custom computing platform indicates that throughput in the order of 20 megabytes per second is achievable on ALgotronix FPGAs if a locally synchronous design style is adopted and global communications minimized. Partial reconfiguration of the datapath at run time, in around 3 seconds, serves to maximize the density of data storage on the machine and correspondingly avoid costly input from the environment
  • Keywords
    database management systems; field programmable gate arrays; information retrieval; pipeline processing; reconfigurable architectures; word processing; ALgotronix FPGAs; SPACE custom computing platform; data storage; document relevance assessment; error tolerance; free text database searching; fully pipelined search machine architecture; global communications; locally synchronous design style; partial reconfiguration; regular expression matching; relevant target words; run time reconfigurable custom computing machines; textual documents; Database searching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    FPGAs for Custom Computing Machines, 1996. Proceedings. IEEE Symposium on
  • Conference_Location
    Napa Valley, CA
  • Print_ISBN
    0-8186-7548-9
  • Type

    conf

  • DOI
    10.1109/FPGA.1996.564737
  • Filename
    564737