AFSEM: Advanced frequent subcircuit extraction method by graph mining approach for optimized cell library developments

Abstract

The optimization of cells and cell combinations used in design is critical to enhance the performance. If frequently used cell combinations are known in advance, a new cell development can be significantly optimized using the cell combinations for chip design. However, extracting frequent cell combinations is an NP hard problem. We propose a new framework, referring as AFSEM, to extract frequent cell combinations for design optimization. To solve this problem, we use a frequent subgraph mining method which is a process of discovering subgraphs. We present an advanced graph modeling and optimized frequent subgraph mining platform for a practical use. The experimental results with various designs demonstrate that the proposed method can discover various types of subcircuits for design optimization with various runtime optimization methods.