Provably good global routing by a new approximation algorithm for multicommodity flow

We show how that new approximation algorithms by Garg and Konemann for the multicommodity flow problem can be modified to solve the linear programming relaxation of the global routing problem. The algorithm presented here also provides a solution of the dual linear problem, thus gives a lower bound on the optimum maximum relative congestion. Our computation results with recent IBM processor chips show that this approach can be used in practice even for large chips and that it is superior on difficult instances where rip-up and reroute algorithms fail.

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