Neural computation network for global routing

Abstract Global routing is a crucial step in circuit layout. Under the constraint of the relative positions of circuit blocks enforced by placement, the global routing develops an effective plan such that the interconnections of nets can be completed efficiently. This problem has been proven to be NP-complete, and most of the currently available algorithms are heuristic. The paper proposes a new neural-computation-network architecture based on the Hopfield and Tank model for the global-routing problem. This network is constructed using two layers of neurons. One layer is used for minimizing the total path length and distributing interconnecting wires evenly between channels. The other layer is used for channel-capacity enforcement. This network is proven to be able to converge to a stable state. A set of randomly generated testing examples are used to verify the performance of the approach. A reduction in total path length of about 20% is attained by this network.

[1]  Richard M. Karp,et al.  Global Wire Routing in Two-Dimensional Arrays (Extended Abstract) , 1983, FOCS.

[2]  Lawrence D. Jackel,et al.  VLSI implementation of a neural network model , 1988, Computer.

[3]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[4]  Carl Sechen,et al.  VLSI Placement and Global Routing Using Simulated Annealing , 1988 .

[5]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[6]  J J Hopfield,et al.  Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Carver Mead,et al.  Analog VLSI and neural systems , 1989 .

[8]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[9]  John J. Hopfield,et al.  Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit , 1986 .

[10]  Pinaki Mazumder,et al.  A Neural Network Design for Circuit Partitioning , 1989, 26th ACM/IEEE Design Automation Conference.

[11]  Scott Kirkpatrick,et al.  Global Wiring by Simulated Annealing , 1983, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[12]  Narsingh Deo,et al.  Graph Theory with Applications to Engineering and Computer Science , 1975, Networks.

[13]  Ran Libeskind-Hadas,et al.  Solutions to the Module Orientation and Rotation Problems by Neural Computation Networks , 1989, 26th ACM/IEEE Design Automation Conference.