Abstract
This paper addresses the problem of circuit clustering for delay minimization, subject to capacity constraints. We use the general delay model, for which only heuristic solutions were unknown. We present an optimal polynomial time algorithm for combinational circuits under this model. Our algorithm can be generalized to solve the problem under any monotone clustering constraint.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - Design Automation Conference |
| Publisher | Publ by IEEE |
| Pages | 309-314 |
| Number of pages | 6 |
| ISBN (Print) | 0897915771 |
| State | Published - 1993 |
| Externally published | Yes |
| Event | Proceedings of the 30th ACM/IEEE Design Automation Conference - Dallas, TX, USA Duration: Jun 14 1993 → Jun 18 1993 |
Other
| Other | Proceedings of the 30th ACM/IEEE Design Automation Conference |
|---|---|
| City | Dallas, TX, USA |
| Period | 6/14/93 → 6/18/93 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Optimal clustering for delay minimization. / Rajaraman, Rajmohan; Wong, Martin D F.
Proceedings - Design Automation Conference. Publ by IEEE, 1993. p. 309-314.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Optimal clustering for delay minimization
AU - Rajaraman, Rajmohan
AU - Wong, Martin D F
PY - 1993
Y1 - 1993
N2 - This paper addresses the problem of circuit clustering for delay minimization, subject to capacity constraints. We use the general delay model, for which only heuristic solutions were unknown. We present an optimal polynomial time algorithm for combinational circuits under this model. Our algorithm can be generalized to solve the problem under any monotone clustering constraint.
AB - This paper addresses the problem of circuit clustering for delay minimization, subject to capacity constraints. We use the general delay model, for which only heuristic solutions were unknown. We present an optimal polynomial time algorithm for combinational circuits under this model. Our algorithm can be generalized to solve the problem under any monotone clustering constraint.
UR - http://www.scopus.com/inward/record.url?scp=0027247165&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0027247165&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0027247165
SN - 0897915771
SP - 309
EP - 314
BT - Proceedings - Design Automation Conference
PB - Publ by IEEE
ER -