Optimal orientations of cells in slicing floorplan designs
Information and Control
Slowing down sorting networks to obtain faster sorting algorithms
Journal of the ACM (JACM)
Dynamic programming with convexity, concavity and sparsity
Theoretical Computer Science - Selected papers of the Combinatorial Pattern Matching School
Finding a minimum weight K-link path in graphs with Monge property and applications
SCG '93 Proceedings of the ninth annual symposium on Computational geometry
Graph-based techniques to speed up floorplan area optimization
Integration, the VLSI Journal
A new area and shape function estimation technique for VLSI layouts
DAC '88 Proceedings of the 25th ACM/IEEE Design Automation Conference
Computing a minimum-weight k-link path in graphs with the concave Monge property
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Applying Parallel Computation Algorithms in the Design of Serial Algorithms
Journal of the ACM (JACM)
PEPPER-a timing driven early floorplanner
ICCD '95 Proceedings of the 1995 International Conference on Computer Design: VLSI in Computers and Processors
DAC '82 Proceedings of the 19th Design Automation Conference
Area minimization for floorplans
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Finding an optimal path without growing the tree
Journal of Algorithms
Hi-index | 0.00 |
As the sizes of many IC design problems become increasingly larger, approximation has become a valuable approach for arriving at satisfactory results without incurring exorbitant computational cost. In this paper, we present several approximation techniques for solving floorplan area minimization problems. These new techniques enable us to reduce both the time and space complexities of the previously best known approximation algorithms by more than a factor of n and n2 for rectangular and L-shaped subfloorplans, respectively (where n is the number of given implementions). The improvements in the time and space complexities of such approximation techniques is critical to their applicability in floorplan area minimization algorithms. The techniques are quite general, and may be applicable to other classes of approximation problems.