Title:
Performance-driven Global Placement via Adaptive Network Characterization

dc.contributor.author Ekpanyapong, Mongkol
dc.contributor.author Lim, Sung Kyu
dc.date.accessioned 2005-03-23T14:53:10Z
dc.date.available 2005-03-23T14:53:10Z
dc.date.issued 2003
dc.description.abstract Delay minimization continues to be an important objective in the design of high-performance computing system. In this paper, we present an effective methodology to guide the delay optimization process of the mincut-based global placement via adaptive sequential network characterization. The contribution of this work is the development of a fully automated approach to determine critical parameters related to performance-driven multi-level partitioning-based global placement with retiming. We validate our approach by incorporating this adaptive method into a state-of-the-art global placer GEO. Our A-GEO, the adaptive version of GEO, achieves 67% maximum and 22% average delay improvement over GEO. en
dc.format.extent 375537 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/5929
dc.language.iso en_US
dc.publisher Georgia Institute of Technology en
dc.relation.ispartofseries CERCS;GIT-CERCS-03-11
dc.subject Adaptive sequential network characterization en
dc.subject A-GEO en
dc.subject Delay optimization en
dc.subject Global placers en
dc.subject High performance computing en
dc.subject Mincut-based global placement en
dc.subject Placement algorithms
dc.title Performance-driven Global Placement via Adaptive Network Characterization en
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.author Lim, Sung Kyu
local.contributor.corporatename Center for Experimental Research in Computer Systems
local.relation.ispartofseries CERCS Technical Report Series
relation.isAuthorOfPublication 31bc3e86-9942-4b3f-aeae-783bb95052ff
relation.isOrgUnitOfPublication 1dd858c0-be27-47fd-873d-208407cf0794
relation.isSeriesOfPublication bc21f6b3-4b86-4b92-8b66-d65d59e12c54
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