Staff View
Knowledge-based Management of Legacy Codes for Automated Design

Descriptive

Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Genre (authority = RULIB-FS)
Other
Genre (authority = marcgt)
technical report
PhysicalDescription
InternetMediaType
application/pdf
Extent
181 p.
Note (type = special display note)
Technical report hpcd-TR-49
Name (type = corporate); (authority = RutgersOrg-School)
NamePart
School of Arts and Sciences (SAS) (New Brunswick)
Name (type = corporate); (authority = RutgersOrg-Department)
NamePart
Computer Science (New Brunswick)
TypeOfResource
Text
TitleInfo
Title
Knowledge-based Management of Legacy Codes for Automated Design
Abstract (type = abstract)
Systems for automated design optimization of complex real-world ob jects can, in principle, be constructed by combining domain-independent numerical routines with existing domain specific analysis and simulation programs. Such legacy" analysis codes are frequently unsuitable for use in automated design. They may crash for large classes of input, be locally non-smooth, or be highly sensitive to control parameters. To be useful, analysis programs must first be modified to reduce or eliminate only the undesired behaviors, without altering the desired computation. To do this by direct modification of the programs is labor-intensive, and necessitates costly re-validation. This dissertation describes research into how legacy analysis codes can be usefully employed in design automation systems. We show that recovery from failure is possible when the failure occurs in the context of a search-based process such as optimization. We discuss the importance of failure context in determining the correct failure recovery action. We then describe an approach to failure recovery that is both context-sensitive and guarantees the integrity of the original computation to which it is applied. We have implemented a high-level language and run-time environment (together called LCM) that allow context-sensitive failure-handling strategies to be incorporated into existing Fortran and C analysis programs while preserving their computational integrity. Our approach relies on globally managing the execution of these programs at the level of discretely callable functions so that the computation is only affected when problems are detected. Problem handling procedures are constructed from a knowledge base of generic problem management strategies. We show that our approach is effective in improving analysis program robustness and design optimization performance in several real-world design domains.
Name (type = personal)
NamePart (type = family)
Keane
NamePart (type = given)
John
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (type = text); (authority = marcrt)
author
OriginInfo
DateCreated (encoding = w3cdtf); (qualifier = exact); (keyDate = yes)
1996-10
RelatedItem (type = host)
TitleInfo
Title
Computer Science (New Brunswick)
Identifier (type = local)
rucore21032500001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3V98CK5
Back to the top

Rights

RightsDeclaration (AUTHORITY = rightsstatements.org); (TYPE = IN COPYRIGHT); (ID = http://rightsstatements.org/vocab/InC/1.0/)
This Item is protected by copyright and/or related rights.You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use.For other uses you need to obtain permission from the rights-holder(s).
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top

Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
Document
CreatingApplication
Version
1.4
ApplicationName
GPL Ghostscript 9.07
DateCreated (point = start); (encoding = w3cdtf); (qualifier = exact)
2018-06-06T12:36:15
DateCreated (point = start); (encoding = w3cdtf); (qualifier = exact)
2018-06-06T12:36:15
Back to the top
Version 8.3.10
Rutgers University Libraries - Copyright ©2019