Publication | Closed Access
Multilevel generalized force-directed method for circuit placement
202
Citations
22
References
2005
Year
Unknown Venue
Numerical AnalysisEngineeringVlsi DesignElectronic Design AutomationComputer ArchitectureInterconnection Network ArchitectureStructural OptimizationComputational MechanicsCircuit PlacementPhysical Design (Electronics)Systems EngineeringMultilevel FrameworkParallel ComputingCombinatorial OptimizationComputational GeometryCircuit AnalysisElectrical EngineeringComputer EngineeringAutomatic Circuit PlacementComputer ScienceNew AlgorithmCircuit DesignParallel Programming
Automatic circuit placement has received renewed interest recently given the rapid increase of circuit complexity, increase of interconnect delay, and potential sub-optimality of existing placement algorithms [13]. In this paper we present a generalized force-directed algorithm embedded in mPL2's [12] multilevel framework. Our new algorithm, named mPL5, produces the shortest wirelength among all published placers with very competitive runtime on the IBM circuits used in [29]. The new contributions and enhancements are: (1) We develop a new analytical placement algorithm using a density constrained minimization formulation which can be viewed as a generalization of the force-directed method in [16]; (2) We analyze and identify the advantages of our new algorithm over the force-directed method; (3) We successfully incorporate the generalized force-directed algorithm into a multilevel framework which significantly improves wirelength and speed. Compared to Capo9.0, our algorithm mPL5 produces 8% shorter wirelength and is 2X faster. Compared to Dragon3.01, mPL5 has 3% shorter wirelength and is 12X faster. Compared to Fengshui5.0, it has 5% shorter wirelength and is 2X faster. Compared to the ultra-fast placement algorithm: FastPlace, mPL5 produces 8% shorter wirelength but is 6X slower. A fast mode of mPL5 (mPL5-fast) can produce 1% shorter wirelength than Fast-Place1.0 and is only 2X slower. Moreover, mPL5-fast has demonstrated better scalability than FastPlace1.0.
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