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B. Lokanathan

dblp:20/2051 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1989
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%
Theoretical computer science
1 paper
Graph algorithms and graph theory · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Electronic design automation › physical design
floorplanning
0.011989
Performance optimized floor planning by graph planarization · DAC 1989
Electronic design automation
physical design
0.011989
Performance optimized floor planning by graph planarization · DAC 1989
Graph algorithms and graph theory › graph theory › graph transformation › graph modification
graph planarization
0.011989
Performance optimized floor planning by graph planarization · DAC 1989

Methods — techniques the papers use, named apart from their topics

rectangular dualization · 0.0linear programming · 0.0
YearPublicationVenuePosition
1989 Performance optimized floor planning by graph planarization
abstract
A new procedure for VLSI floor planning that minimizes routing parasitics is presented. The procedure, based on rectangular dualization, maximizes adjacency of modules that are heavily connected or connected by critical nets. Wiring macros are introduced to provide routing area for those modules that cannot be located adjacent to one another; these macros are located by planarizing the system interconnectivity graph using an edge crossing strategy that minimizes the cost of intersection. The rectangular dual is compacted using heuristics to approximate a quadratic area constraint by one or more linear constraints, thereby reducing the complexity of compaction from that of quadratic programming to linear programming.
B. Lokanathan, Edwin Kinnen
DAC1