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Congestion Reduction During Placement with Provably Good Approximation Bound by X. Yang; M. Wang; R. Kastner; S. Ghiasi; M. Sarrafzadeh is a Computer Science article available to read on EtoBox.

What is Congestion Reduction During Placement with Provably Good Approximation Bound about?

This paper presents a novel method to reduce routing congestion during placement stage. The proposed approach is used as a post-processing step in placement. Congestion reduction is based on local improvement on the existing layout. However, the approach has a global view of the congestion over the entire design. It uses integer linear programming (ILP) to formulate the problem of conflicts between multiple congested regions, and performs local improvement according to the solution of the ILP problem. The approximation algorithm of the formulated ILP problem is studied and good approximation bounds are given and proved. Experiments show that the proposed approach can effectively alleviate the congestion of global routing results. The low computational complexity of the proposed approach indicates its scalability on large designs.

Who reads Congestion Reduction During Placement with Provably Good Approximation Bound?

Author

X. Yang; M. Wang; R. Kastner; S. Ghiasi; M. Sarrafzadeh

Publisher

Association for Computing Machinery; Association for Computing Machinery (ACM) (ISSN 1084-4309)

Published

2003

Language

EN

Field

Computer Science (Physical Sciences)