Publication | Closed Access
Cell density-driven detailed placement with displacement constraint
51
Citations
13
References
2014
Year
Unknown Venue
EngineeringComputer ArchitectureComputer-aided DesignBiomedical EngineeringStructural OptimizationDisplacement ConstraintSystems EngineeringSensor PlacementCombinatorial OptimizationComputational GeometryGeometric ModelingModern Placement ProcessDetailed PlacementComputer EngineeringComputer ScienceCell ManipulationCell EngineeringCell BiologyGlobal PlacementPattern FormationCell DetectionMedicineMultiscale Modeling
Modern placement process involves global placement, legalization, and detailed placement. Global placement produce a placement solution with minimized target objective, which is usually wire-length, routability, timing, etc. Legalization removes cell overlap and aligns the cells to the placement sites. Detailed placement further improves the solution by relocating cells. Since target objectives like wire-length and timing are optimized in global placement, legalization and detailed placement should not only minimize their own objectives but also preserve the global placement solution. In this paper, we propose a detailed placement algorithm for minimizing wire-length, while preserving the global placement solution by cell displacement constraint and target cell density objective. Our detailed placer involves two steps: Global Move that allocates each cell into a bin/region that minimizes wire-length, while not overflowing the target cell density. Local Move that finely adjust the cell locations in local regions to further minimize the wire-length objective. With large-scale benchmarks from ICCAD 2013 detailed placement contest, the results show that our detailed placer, RippleDP, can improve the global placement results by 13.38% - 16.41% on average under displacement constraint and target placement density objective.
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