Research On Hardware/Software Partitioning Technology Method Of Embedded System

Hardware/software partitioning is the process of dividing an application into software running on a microprocessor and hardware coprocessors. In recent years, embedded systems have evolved into complex multifunction systems implemented using a mix of both hardware and software. The allocation of the system functionality into hardware and software components has a significant impact on the system performance.During the whole process of HW/SW co-design, the HW/SW partitioning algorithm is a key technology. A good algorithm can get a better solution in a short time. This paper mainly do two contributions, one is investigate the application of the Particle Swarm Optimization echnique for solving the Hardware/software partitioning problem and another is proposes a Hardware/software partitioning algorithm based on a parallel K-means clustering and greedy.We investigate the application of the Particle Swarm Optimization (PSO) technique for solving the Hardware/software partitioning problem. The PSO is attractive for the Hardware/software partitioning problem as it offers reasonable coverage of the design space together with O(n) excution time, where n is the number of proposed solutions that provide the final solution. We found that PSO outperforms GA in the cost function and the execution time. To further enhance the quality of the results, we cascading the two algorithms (PSO followed by PSO).In order to solve Hardware/software partitioning based on resource constraint. The paper put forward a method which was based on greedy algorithm. First, this algorithm assembles task vertex with similar attribute to form a bigger new task vertex based on parallel K-means clustering, and then partitions hardware/software based on greedy algorithm. The experiments showed this algorithm has high efficiency to the multi-duties pitch point complex duty.