A Behavioral Type Inference System for Compositional System-on-Chip Design

Abstract : The design productivity gap has been recognized by the semiconductor industry as one of the major threats to the continued growth of system-on-chips and embedded systems. Ad-hoc system-level design methodologies, that lifts modeling to higher levels of abstraction, and the concept of intellectual property (IP), that promotes reuse of existing components, are essential steps to manage design complexity. However, the issue of compositional correctness arises with these steps. Given components from different manufacturers, designed with heterogeneous models, at different levels of abstraction, assembling them in a correct-by-construction manner is a difficult challenge. We address this challenge by proposing a process algebraic model to support system design with a formal model of computation and serve as a behavioral type system to capture the behavior of system components at the interface level. The proposed type system is conceptually minimal and supports a scalable notion and a flexible degree of abstraction. Our presentation targets the de facto standard SystemC, yet with a generic and language-independent method. Applications of our technique range from the detection of local design errors to the compositional assembly of modules.
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Jean-Pierre Talpin, David Berner, Sandeep Shukla, Paul Le Guernic, Abdoulaye Gamatié, et al.. A Behavioral Type Inference System for Compositional System-on-Chip Design. Fourth International Conference on Application of Concurrency to System Design (ACSD'04), Jun 2004, Hamilton, Ontario, Canada. pp.47-56, ⟨10.1109/CSD.2004.1309115⟩. ⟨hal-00542146⟩



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