Rules-Based Object Clustering: A Data Structure for Symbolic VLSI Synthesis and Analysis

Object clustering is a data structure expressly binding analysis to support the incremental symbolic synthesis of high performance VLSI devices. Utilization of abstraction allows technology independent and technology dependent design entities to be represented as symbolic objects. This data structure supports a hierarchical representation of a VLSI device that equally applies to top-down or bottom-up synthesis. Processing concurrency is exploited in an interactive design environment centered around commercially available CAD work stations. As the designer is interactively composing the symbolic representation of circuit topology to implement a specific function, a rules-based algorithm performs the integration of the new object into the existing object clustering data structure. Neighboring relationships between objects are determined by hierarchical object-pair intersection and underly the algorithms performing electrical and physical design rule checking, node topology extraction for circuit analysis, logic simulation, and testability analysis, and mask geometries generation. Object clustering is a robust data structure ideally suited to symbolically represent VLSI device designs, while facilitating analytical exploration and incremental synthesis.