The codesign is a robust methodology, used in modern embedded systems with the objective of achieving the functional specifications and meeting the non-functional requirements. The most interesting step in the codesing is the process of Hardware/Software Partitioning. The aim is to decide which functionalities of the system should be implemented in hardware ($HW$) or in software ($SW$). In this article, a new heuristic algorithm is proposed to simultaneously optimize the hardware area (cost) and the execution time (performance) of a multiprocessor system. The proposed algorithm is inspired from game theory and especially from the GO game. The system is modeled using the DAG graph (Data Acyclic Graph), and two players (HW player and SW player) play in turn and choose a block (functionality) from the graph (system). The HW player has the goal of optimizing the global HW area while the SW player has the objective of minimizing the global execution time. After the game termination, and based on the 0-1 Knapsack algorithm, a step of refinement is used to meet the constraint on the total hardware area or on the overall execution time if a constraint is pre-defined. Experimental results show that the proposed algorithm gives better solutions compared to the Simulated Annealing algorithm and the Genetic Algorithm.
Online hardware/software partitioning in networked embedded systems
