ComPLx: A Competitive Primal-dual Lagrange Optimization for Global Placement

We develop a projected-subgradient primal-dual Lagrange optimization for global placement, that can be instantiated with a variety of interconnect models. It decomposes the original non-convex problem into\more convex"sub-problems. It generalizes the recent SimPL, SimPLR and Ripple algo- rithms...

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Bibliographic Details
Published in:DAC Design Automation Conference 2012 pp. 747 - 752
Main Authors: Kim, Myung-Chul, Markov, Igor L.
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 03.06.2012
IEEE
Series:ACM Conferences
Subjects:
Algorithm design and analysis
Algorithms
Applied computing > Physical sciences and engineering
Applied computing > Physical sciences and engineering > Mathematics and statistics
Approximation methods
Benchmark testing
Computing methodologies > Modeling and simulation
Convergence
Layout
Mathematics of computing > Mathematical analysis > Numerical analysis
Optimization
physical design
placement
Runtime
SPICE
Saint-Venant equations
dynamic river network simulation
ISBN:1450311997, 9781450311991
ISSN:0738-100X
Online Access:Get full text
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Summary:We develop a projected-subgradient primal-dual Lagrange optimization for global placement, that can be instantiated with a variety of interconnect models. It decomposes the original non-convex problem into\more convex"sub-problems. It generalizes the recent SimPL, SimPLR and Ripple algo- rithms and extends them. Empirically, ComPLx outper- forms all published placers in runtime and performance on ISPD 2005 and 2006 benchmarks.
ISBN:1450311997
9781450311991
ISSN:0738-100X
DOI:10.1145/2228360.2228496