Integrated circuit floorplanning method based on moving block sequence and multi-agent particle swarm

Abstract

The invention discloses an integrated circuit floorplanning method based on a moving block sequence and a multi-agent particle swarm, and belongs to the technical field of physical design floorplanning. The moving block sequence is used as an encoding method, a multi-agent system and a particle swarm algorithm are combined, and the integrated circuit floorplanning method is used for solving the integrated circuit floorplanning problem. The integrated circuit floorplanning method is characterized in that firstly, each agent in an agent grid is initialized according to an adopted random generation method, then the moving block sequence is designed to encode each agent, and a neighbourhood competition operator, the particle swarm algorithm and a self-learning operator are designed at last to optimize the agents. Verification results show that the integrated circuit floorplanning method has advantages on one important aspect of methods and effectiveness for evaluating and solving the integrated circuit floorplanning problem, namely, the minimum rectangular coverage area, and the method effectively solves the integrated circuit floorplanning problem and can be expanded to solve multi-objective integrated circuit floorplanning problems.

Description

Technical field [0001] The present invention relates to a method for physical design layout planning, in particular to an integrated circuit layout method based on moving block sequence (MBS) and multi-agent particle swarm optimization (MAPSO) . Background technique [0002] Floorplanning is a key link in the physical design of very large scale integration (VLSI), and its results have an important impact on the size of the final chip and the global interconnect structure. With the rapid development of technology, the complexity of chip design is increasing rapidly, and the requirements for chip size and internal interconnection performance are also getting higher and higher, which makes the role of layout planning particularly important. For the layout planning problem, many scholars have put forward a variety of algorithms using different mathematical tools, including minimum segmentation algorithms, hierarchical design methods, analytical algorithms, and random optimization al...

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Problems solved by technology

Here, it is mainly considered that the search space of the stochastic optimization method represented by the non-binary distribution graph is non-convex, which is not conducive to the evolutionary algorithm, and its storage capacity is also large

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