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Abstract: Congestion estimation is an important issue for design automation of the VLSI layout. Fast congestion estimation provides an efficient means to adjust the placement and wire planning. A probabilistic model of interconnections enables designers to quickly predict routing congestion. We propose a powerful and fast estimation approach that allows wires to have bounded-length detours to bypass congestions. The method is more realistic and precise than the previous work. The experimental results demonstrate the effectiveness of the method on routing benchmarks. [Copyright &y& Elsevier]

Interconnect congestion estimation plays an important role in the physical design of integrated circuits. Fast congestion analysis prior to global routing enhances the placement quality and improves the routability for the subsequent routing phases. This article presents a novel congestion estimation method for a wire layout with bounded detours and bends. Experimental results on benchmarks demonstrate the efficiency and accuracy of our approach. [ABSTRACT FROM AUTHOR]

Abstract: Congestion estimation plays an important role in the physical layout of VLSI design. This paper presents a new probabilistic estimation model that improves the previous estimators by relaxing the constraint on detours in a route. The model is more general and realistic for it gives the flexibility for the wires to have wider usage area to bypass the congestion regions and blockages. Given a routing grid and a set of nets to be routed, the model predicts the routing density on each edge of the grid. The routing density provides direct congestion estimation. We compare our estimation results to the actual routing results. Experimental results show the effectiveness of our estimator. [Copyright &y& Elsevier]

Interconnect planning is an important issue in VLSI designs. Routing congestion is an important problem during placement. This paper presents a novel approach to estimating the routing congestion on the hexagonal model with bounded-length detours. It is the first probabilistic estimation work on hexagonal topologies. A combinatorial estimation algorithm is presented. The experimental results demonstrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]