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Title: US5742814: Background memory allocation for multi-dimensional signal processing
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Country: US United States of America

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74 pages

 
Inventor: Balasa, Florin; Tustin Ranch, CA
Catthoor, Francky; Temse, Belgium
De Man, Hugo; Kessel-lo, Belgium

Assignee: IMEC vzw, Leuven, Belgium
other patents from INTERUNIVERSITAIR MICRO-ELEKTRONICA CENTRUM (IMEC VZW) (749624) (approx. 301)
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Published / Filed: 1998-04-21 / 1996-05-15

Application Number: US1996000649903

IPC Code: Advanced: G06F 9/50; H04N 7/26;
Core: G06F 9/46; more...
IPC-7: G06F 17/30;

ECLA Code: G06F9/50A2M; H04N7/26L4;

U.S. Class: Current: 707/102; 375/E07.1; 707/104.1; 717/155;
Original: 395/613; 395/615; 395/709;

Field of Search: 395/006,70

Priority Number:
1996-05-15  US1996000649903
1995-11-06  US1995000007288
1995-11-01  US1995000007160P

Abstract:     Data storage and transfer cost is responsible for a large amount of the VLSI system realization cost in terms of area and power consumption for real-time multi-dimensional signal processing applications. Applications or this type are data-dominated because they handle a large amount of indexed data which are produced and consumed in the context of nested loops. This important application domain includes the majority of speech, video, image, and graphic processing (multi-media in general) and end-user telecom applications. The present invention relates to the automated allocation of the background memory units, necessary to store the large multi-dimensional signals. In order to handle both procedural and nonprocedural specification, the novel memory allocation methodology is based on an optimization process driven by data-flow analysis. This steering mechanism allows more exploration freedom than the more restricted scheduling-based investigation in the existent synthesis systems. Moreover, by means of an original polyhedral model of data-flow analysis, the novel allocation methodology can accurately deal with complex specifications, containing large multi-dimensional signals. The class of specifications handled by this polyhedral model covers a larger range than the conventional ones, i.e. the entire class of affine representations. Employing estimated silicon area or power consumption costs yielded by recent models for on-chip memories, the novel allocation methodology produces one, or optionally, several distributed multi-port memory architecture(s) with fully-determined characteristics, complying with a given clock cycle budget for memory operations.

Attorney, Agent or Firm: Knobbe, Martens, Olson & Bear, LLP ;

Primary / Asst. Examiners: Amsbury, Wayne;

INPADOC Legal Status: Show legal status actions

Family: None

First Claim:
Show all 46 claims
What is claimed:     1. A method of generating a data-flow graph representative of data to be stored in a data-dominated processing system, comprising the steps of:
  • partitioning a plurality of linearly bounded lattices representative of data into partitioned linearly bounded lattices comprising basic sets and disjoint linearly bounded lattices;
  • deriving a plurality of dependency relations between the partitioned linearly bounded lattices; and
  • constructing a data-flow graph having a plurality of nodes, each node representing one of the partitioned linearly bounded lattices, and a plurality of arcs, each arc representing one of the dependency relations.


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Forward References: Show 29 U.S. patent(s) that reference this one

       
U.S. References: Go to Result Set: All U.S. references   |  Forward references (29)   |   Backward references (6)   |   Citation Link

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Foreign References: None

Other Abstract Info: DERABS G1998-260882 DERABS G1998-260882

Other References:
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  • "Background Memory Allocation in Multidimensional Signal Processing," Balasa, F., Ph.D. thesis, IMEC, Nov. 1995.
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