Electrical computers and digital processing systems: memory – Storage accessing and control – Hierarchical memories
Reexamination Certificate
2011-03-01
2011-03-01
Ellis, Kevin L (Department: 2187)
Electrical computers and digital processing systems: memory
Storage accessing and control
Hierarchical memories
C711S170000, C712S207000
Reexamination Certificate
active
07899996
ABSTRACT:
Adaptively pre-fetching data includes collecting a first set of statistics based on a number of avoidable read-misses in which data exists that is prior to data being read, collecting a second set of statistics based on a number of avoidable read-misses in which data exists that follows data being read, and collecting a third set of statistics based on said first and second sets of statistics. On the basis of the second set of statistics, a pre-fetch technique is selected from a first technique that pre-fetches data following data being read and a second technique that pre-fetches data before and following the data being read. The first and third set of statistics may be used to determine when to pre-fetch data.
REFERENCES:
patent: 5206939 (1993-04-01), Yanai et al.
patent: 5778394 (1998-07-01), Galtzur et al.
patent: 5845147 (1998-12-01), Vishlitzky et al.
patent: 5857208 (1999-01-01), Ofek
patent: 5941981 (1999-08-01), Tran
patent: 6003114 (1999-12-01), Bachmat
patent: 6085287 (2000-07-01), O'Neil et al.
patent: 6098153 (2000-08-01), Fuld et al.
patent: 6529998 (2003-03-01), Yochai et al.
patent: 6961824 (2005-11-01), Rowlands et al.
Bradley Matthew
Ellis Kevin L
EMC Corporation
Muirhead and Saturnelli LLC
LandOfFree
Full track read for adaptive pre-fetching of data does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Full track read for adaptive pre-fetching of data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Full track read for adaptive pre-fetching of data will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2711802