Modeling methodology for integrated simulation of embedded systems

  • Authors:

  • Akos Ledeczi;James Davis;Sandeep Neema;Aditya Agrawal

  • Affiliations:

  • Vanderbilt University, Nashville, TN;Vanderbilt University, Nashville, TN;Vanderbilt University, Nashville, TN;Vanderbilt University, Nashville, TN

  • Venue:
  • ACM Transactions on Modeling and Computer Simulation (TOMACS)
  • Year:
  • 2003

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Abstract

Developing a single embedded application involves a multitude of different development tools including several different simulators. Most tools use different abstractions, have their own formalisms to represent the system under development, utilize different input and output data formats, and have their own semantics. A unified environment that allows capturing the system in one place and one that drives all necessary simulators and analysis tools from this shared representation needs a common representation technology that must support several different abstractions and formalisms seamlessly. Describing the individual formalisms by metamodels and carefully composing them is the underlying technology behind MILAN, a Model-based Integrated Simulation Framework. MILAN is an extensible framework that supports multigranular simulation of embedded systems by seamlessly integrating existing simulators into a unified environment. Formal metamodels and explicit constraints define the domain-specific modeling language developed for MILAN that combines hierarchical, heterogeneous, parametric dataflow representation with strong data typing. Multiple modeling aspects separate orthogonal concepts. The language also allows the representation of the design space of the application, not just a point solution. Nonfunctional requirements are captured as formal, application-specific constraints. MILAN has integrated tool support for design-space exploration and pruning. The models are used to automatically configure the integrated functional simulators, high-level performance and power estimators, cycle-accurate performance simulators, and power-aware simulators. Simulation results are used to automatically update the system models. The article focuses on the modeling methodology and briefly describes how the integrated models are utilized in the framework.