Multilevel circuit partitioning
DAC '97 Proceedings of the 34th annual Design Automation Conference
Algorithms for large-scale flat placement
DAC '97 Proceedings of the 34th annual Design Automation Conference
Partitioning-based standard-cell global placement with an exact objective
Proceedings of the 1997 international symposium on Physical design
Generic global placement and floorplanning
DAC '98 Proceedings of the 35th annual Design Automation Conference
Proud: a fast sea-of-gates placement algorithm
DAC '88 Proceedings of the 25th ACM/IEEE Design Automation Conference
Can recursive bisection alone produce routable placements?
Proceedings of the 37th Annual Design Automation Conference
Improved cut sequences for partitioning based placement
Proceedings of the 38th annual Design Automation Conference
Dragon2000: standard-cell placement tool for large industry circuits
Proceedings of the 2000 IEEE/ACM international conference on Computer-aided design
Free space management for cut-based placement
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Efficient and effective placement for very large circuits
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A tale of two nets: studies of wirelength progression in physical design
Proceedings of the 2006 international workshop on System-level interconnect prediction
Computational geometry based placement migration
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
A morphing approach to address placement stability
Proceedings of the 2007 international symposium on Physical design
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To achieve timing closure, one often has to run through several iterations of physical synthesis flows, for which placement is a critical step. During these iterations, one hopes to consistently move towards design convergence. A placement algorithm that is "stable" will consistently drive towards similar solutions, even with changes in the input netlist and placement parameters. Indeed, the stability of the algorithm is arguably as important a characteristic as the wirelength it achieves. However, currently there is no way to actually quantify the stability of a placement algorithm. This work seeks to address the issue by proposing metrics that measure the stability of a placement algorithm. Our experimental results examine the stability of three different placement algorithms with our proposed metrics and convincingly illustrate that some algorithms are quantifiably more stable than others. We believe that this opens the door to applying different standards for evaluating placement algorithms in terms of their effectiveness for achieving timing closure.