Efficient design space exploration for component-based system design

As the technology scaling down continues to go beyond 22nm, the increasing transistor density on a single die is leading towards more and more complex systems-on-chip. Designers are faced with the challenge of how to efficiently design such a complicated system with tight time-to-market constraints. Component-based system design and design space exploration are two key techniques to overcoming the challenge. In this paper, we model the design space exploration of a system with difference constraints as a bi-criteria convex cost flow problem and develop an efficient solver for it based on parametric simplex method. Furthermore, considering the high cost of synthesizing the underlying soft IP cores, we propose an online algorithm to incrementally refine the system-level Pareto curves as more component-wise sampling points are added. The experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.