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Algorithmic aspects for functional partitioning and scheduling in hardware/software co-design

机译:硬件/软件协同设计中功能分区和调度的算法方面

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摘要

Hardware/software (HW/SW) partitioning and scheduling are the crucial steps during HW/SW co-design. It has been shown that they are classical combinatorial optimization problems. Due to the possible sequential or concurrent execution of the tasks, HW/SW partitioning and scheduling has become more difficult to solve optimally. In this paper more efficient heuristic algorithms are proposed for the HW/SW partitioning and scheduling. The proposed algorithm partitions a task graph by iteratively moving the task with highest benefit-to-area ratio in higher priority. The benefit-to-area ratio is updated in each iteration step to cater for the task concurrence. The proposed algorithm for task scheduling executes the task lying in hardware-only critical path in higher priority to enhance the task forecast. A large body of experimental results conclusively shows that the proposed heuristic algorithm for partitioning is superior to the latest efficient combinatorial algorithm (Tabu search) cited in this paper. Moreover, the Tabu search for partitioning has been further improved by utilizing the proposed heuristic solution as its initial solution. In addition, the proposed scheduling algorithm obtains the improvements over the most widely used approaches by up to 10% without large increase in running time.
机译:硬件/软件(HW / SW)的分区和调度是HW / SW协同设计中的关键步骤。已经证明它们是经典的组合优化问题。由于可能依次执行任务或并发执行任务,因此,硬件/软件分区和调度变得更加难以最佳解决。在本文中,针对硬件/软件分区和调度提出了更有效的启发式算法。所提出的算法通过以更高的优先级迭代移动具有最高受益面积比的任务来划分任务图。在每个迭代步骤中都会更新效益面积比,以满足任务的并发性。所提出的任务调度算法以较高的优先级执行仅位于硬件的关键路径中的任务,以增强任务预测。大量的实验结果最终表明,所提出的启发式分区算法优于本文引用的最新高效组合算法(Tabu搜索)。此外,通过使用提议的启发式解决方案作为其初始解决方案,对禁忌的分区搜索有了进一步的改进。另外,所提出的调度算法在不大大增加运行时间的情况下获得了对最广泛使用的方法的多达10%的改进。

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