Monterey Design Systems, Inc.

Synopsys, Inc.

Dennis Yamamoto

Lawrence Thomas Pileggi

Douglas B Boyle

Majid Sarrafzadeh

Salil Ravindra Raje

Sharad Malik

Gary K Yeap

Feroze P Taraporevala

Abhijeet Chakraborty

Lilly Shieh

James S Koford

Christopher J Dunn

David Gluss

Robert E Shortt

Tong Gao

Dinesh D Gaitonde

Joseph T Rahmeh

Eric McCaughrin

Emre Tuncer

Archie Li

Yau-Tsun Steven Li

Satamurthy Pullela

Sam Jung Kim

The present invention, generally speaking, provides a placement method for the physical design of integrated circuits in which natural topological feature clusters (topo-clusters) are discovered and exploited during the placement process. Topo-clusters may be formed based on various criteria including, for example, functional similarity, proximity (in terms of number of nets), and genus. Genus refers to a representation of a netlist in terms of a number of planar netlists&#x2014;netlists in which no crossing of nets occurs. Topo-clusters drive initial placement, with all of the gates of a topo-cluster being placed initially in a single bin of the placement layout or within a group of positionally-related bins. The portion of a topo-cluster placed within a given bin is called a quanto-cluster. An iterative placement refinement process then follows, using a technique referred to herein as Geometrically-Bounded FM (GBFM), and in particular Dual GBFM. In GBFM, FM is applied on a local basis to windows encompassing some number of bins. From iteration to iteration, windows may shift position and vary in size. When a region bounded by a window meets a specified cost threshold in terms of a specified cost function, that region does not participate. The cost function takes account of actual physical metrics&#x2014;delay, area, congestion, power, etc. 'Dual' refers to the fact that each iteration has two phases. During a first phase, FM is performed within a region on a quanto-cluster basis. During a second phase, FM is performed within the region on a gate basis. GBFM occurs in the context of recursive quadrisection. Hence, after GBFM has been completed, a further quadrisection step is performed in which each bin is divided into four bins, with a quarter of the gates of the original bin being placed in the center of each of the resulting bins. GBFM then follows, and the cycle repeats until each bin contains a fairly small number of gates. Following the foregoing global placement process, the circuit is then ready for detailed placement in which cells are assigned to placement rows.

Placement method for integrated circuit design using topo-clustering

The disclosure describes a placement method for the physical design of integrated circuits in which natural topological feature clusters are discovered and exploited during the placement process is disclosed. Topo-clusters drive initial placement, with all of the gates of a topo-cluster being placed initially in a single bin of the placement layout or within a group of positionally-related bins. An iterative placement refinement process is done using a technique referred to as Dual Geometrically-Bounded FM (GBFM). GBFM is applied on a local basis to windows encompassing a number of bins. From iteration to iteration, windows may shift position and vary in size. When a region bounded by a window meets a specified cost threshold in terms of a specified cost function, that region stops participating. Following the foregoing global placement process the circuit is then ready for detailed placement in which cells are assigned to placement rows.

A method for design optimization using logical and physical information is provided. In one embodiment, a method for design optimization using logical and physical information, includes receiving a behavioral description of an integrated circuit or a portion of an integrated circuit, optimizing placement of circuit elements in accordance with a first cost function, and optimizing logic of the circuit elements in accordance with a second cost function, in which the optimizing placement of the circuit elements and the optimizing logic of the circuit elements are performed concurrently. The method can further include optimizing routing in accordance with a third cost function, in which the optimizing routing, the optimizing placement of the circuit elements, and the optimizing logic of the circuit elements are performed concurrently.

Method for design optimization using logical and physical information

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Los Altos, CA, United States of America

Dennis Yamamoto