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K. Mohanram

dblp:91/6363 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

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

Systems, architecture and hardware · 1

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
Automated reasoning and model checking · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Electronic design automation › logic synthesis
boolean function representation
0.012000
Analysis of composition complexity and how to obtain smaller canonical graphs · DAC 2000
Electronic design automation
hardware verification and test
0.012000
Analysis of composition complexity and how to obtain smaller canonical graphs · DAC 2000
Electronic design automation › logic synthesis › switching theory
finite state machine analysis
0.012000
Analysis of composition complexity and how to obtain smaller canonical graphs · DAC 2000

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

dynamic partitioning · 0.1composition · 0.1
YearPublicationVenuePosition
2000 Analysis of composition complexity and how to obtain smaller canonical graphs
abstract
We discuss an open problem in ROBDD construction using composition and prove that the worst case complexity of the construction is truly cubic. With this insight we show that the process of composition naturally leads to construction of (even exponentially) compact partitioned-OBDDs (POBDDs)[17]. Our algorithm which incorporates dynamic partitioning, leads to the most general (and compact) form of POBDDs - graphs with multiple root variables. To show our algorithm is robust and practical, we have analyzed some well known problems in Boolean function representation, verification and finite state machine analysis where our approach generates graphs which are even orders of magnitude smaller.
Jawahar Jain, K. Mohanram, Dinos Moundanos, Ingo Wegener, Yuan Lu 0004
DAC2