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OPTIMIZING MEMORY HIERARCHY IN MACHINE VISION COMPUTERS

Award Information

Agency:
National Science Foundation
Branch:
N/A
Award ID:
7457
Program Year/Program:
1988 / SBIR
Agency Tracking Number:
7457
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
American Cimflex Corpon
11 Industry Drive Pittsburgh, PA 15275
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 1988
Title: OPTIMIZING MEMORY HIERARCHY IN MACHINE VISION COMPUTERS
Agency: NSF
Contract: N/A
Award Amount: $50,000.00
 

Abstract:

THIS WORK PROPOSES AN INVESTIGATION AND CHARACTERIZATION OF IMAGE PROCESSING ALGORITHMS AND THEIR RELATIONSHIP TO IMAGE REPRESENTATION SCHEMES. CLASSIC IMAGE PROCESSING FUNCTIONS MANIFEST SIGNIFICANT DIFFERENCES IN MEMORY ACCESS PATTERNS, I.E. SPATIAL AND TEMPORAL LOCALITY, FROM THE STANDARD 'GENERAL PURPOSE' ROUTINES WHICH HAVE HISTORICALLY BEEN USED AS THE METRICS OF OPTIMAL SYSTEM DESIGN. IMAGE PROCESSING ALGORITHMS HAVE NOT BEEN CHARACTERIZED AS A SEPARATE CLASS OF FUNCTIONS EXECUTING IN A UNIPROCESSOR SYSTEM. IT IS POSTULATED THAT IMPORTANT INCREASES IN PERFORMANCE CAN BE OBTAINED BY CUSTOMIZATION OF THE COMPUTING ARCHITECTURE. THIS ENHANCED PERFORMANCE WILL BE OBTAINED WITHOUT RESORTING TO HIGHLY PARALLEL SYSTEMS AND THE RESULTING PROBLEMS OF DECREASED MEAN TIME BETWEEN FAILURES AND HIGHLY COMPLEX PROGRAMMING ISSUES. ITEMS TO BE STUDIED ARE MEMORY HIERARCHY AND CACHING STRATEGIES AS WELL AS STORED IMAGE REPRESENTATION SCHEMES. USING STOCHASTIC MODELS OF BEHAVIOR AN OPTIMAL IMAGE PROCESSING ARCHITECTURE AND STORED IMAGE REPRESENTATION SCHEME WILL BE DESIGNED.

Principal Investigator:

Jeffrey l nye
0

Business Contact:

Small Business Information at Submission:

American Cimflex Corpon
11 Industry Drive Pittsburgh, PA 15275

EIN/Tax ID:
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No