A New Optimization Technique for Improving Resource Exploitation and Critical Path Minimization

dc.contributor.authorLandwehr, Birgerde
dc.contributor.authorMarwedel, Peterde
dc.date.accessioned2004-12-06T12:57:04Z
dc.date.available2004-12-06T12:57:04Z
dc.date.created1997de
dc.date.issued1998-07-04de
dc.description.abstractThis paper presents a novel approach to algebraic optimization of data-flow graphs in the domain of computationally intensive applications. The presented approach is based upon the paradigm of simulated evolution which has been proven to be a powerful method for solving large non-linear optimization problems. We introduce a genetic algorithm with a new chromosomal representation of data-flow graphs that serves as a basis for preserving the correctness of algebraic transformations and allows an efficient implementation of the genetic operators. Furthermore, we introduce a new class of hardware-related transformation rules which for the first time allow to take existing component libraries into account. The efficiency of our method is demonstrated by encouraging experimental results for several standard benchmarks.en
dc.format.extent1873475 bytes
dc.format.extent677184 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/2003/2749
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-7698
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.subject.ddc004de
dc.titleA New Optimization Technique for Improving Resource Exploitation and Critical Path Minimizationen
dc.typeTextde
dc.type.publicationtypeconferenceObject
dcterms.accessRightsopen access

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