Algorithmic Aspects of Hardware/Software Partitioning: 1D Search Algorithms

Abstract

Hardware/software (HW/SW) partitioning is one of the key challenges in HW/SW codesign. This paper presents efficient algorithms for the HW/SW partitioning problem, which has been proved to be NP-hard. We reduce the HW/SW partitioning problem to a variation of knapsack problem that is approximately solved by searching 1D solution space, instead of searching 2D solution space in the latest work cited in this paper, to reduce time complexity. Three heuristic algorithms are proposed to determine suitable partitions to satisfy HW/SW partitioning constraints. We have shown that the time complexity for partitioning a graph with n nodes and m edges is significantly reduced from O(dx · dy · n3) to O(n log n + d · (n + m)), where d and dx · dy are the number of the fragments of the searched 1D solution space and the searched 2D solution space, respectively. The lower bound on the solution quality is also proposed based on the new computing model to show that it is comparable to that reported in the literature. Moreover, empirical results show that the proposed algorithms produce comparable and often better solutions when compared to the latest algorithm while reducing the time complexity significantly.