Framework for hardware/software partitioning utilizing Bayesian belief networks

In heterogeneous systems design, partitioning of the functional specifications into hardware and software components is an important procedure. Often, a hardware platform is chosen and the software is mapped onto the existing partial solution, or the actual partitioning is performed in an ad hoc manner. The partitioning approach presented is novel in that it uses Bayesian belief networks (BBNs) to categorize functional components into hardware and software classifications. First, the motivation and background material are presented. Then, a case study of a programmable thermostat is developed to illustrate the BBN approach. The outcomes of the partitioning process are discussed and placed in a larger design context, called model-based co-design.