查询结果:   朱峰军,武继刚,宋庆增.多选择软硬件划分问题的启发式算法比较[J].计算机应用与软件,2015,32(2):215 - 219.
中文标题
多选择软硬件划分问题的启发式算法比较
发表栏目
嵌入式软件与应用
摘要点击数
1083
英文标题
HEURISTIC ALGORITHMS COMPARISONS FOR MULTIPLE-CHOICE HARDWARE/SOFTWARE PARTITIONING
作 者
朱峰军 武继刚 宋庆增 Zhu Fengjun Wu Jigang Song Qingzeng
作者单位
天津工业大学计算机科学与软件学院 天津 300387     
英文单位
School of Computer Science and Software, Tianjin Polytechnic University, Tianjin 300387, China     
关键词
多选择软硬件划分 模拟退火 遗传算法 禁忌搜索
Keywords
Multiple-choice hardware/software partitioning Simulated annealing Genetic algorithm Tabu search
基金项目
国家自然科学基金项目(61173032)
作者资料
朱峰军,硕士生,主研领域:软硬件协同设计。武继刚,教授。宋庆增,讲师。 。
文章摘要
软硬件协同设计作为嵌入式系统开发的重要技术,随着嵌入式系统的广泛应用变得越来越重要。软硬件划分是软硬件协同设计的关键环节,是经典的组合优化问题,已被证明是NP完全问题。对于一个给定的任务而言,由于在硬件实现中存在并行执行的潜力,具有不同面积的硬件可以提供不同的执行速度。这样,一个任务根据可利用的硬件面积可以有多种硬件实现方式。现有的软硬件划分方法通常仅仅考虑单一的硬件实现方式,却忽略了多种选择的硬件实现方式。对于多选择的软硬件划分问题,分别使用模拟退火算法和遗传算法,提出了可行性的解决方案?⒂虢伤阉魉惴ń斜冉希罢叶嘌≡袢碛布治侍獾南喽越虾玫钠舴⑹剿惴āJ笛榻峁砻鳎谇蟮玫慕獾闹柿糠矫妫伤阉魉惴ㄏ啾扔谄渌街炙惴ǘ允亲詈玫?在获得较好解的速度方面,模拟退火算法和遗传算法要比禁忌搜索算法快得多。
Abstract
As the important technique of embedded system development, hardware/software (HW/SW) co-design is becoming increasingly important along with the widespread applications of embedded systems. Hardware/software partitioning is the crucial step in HW/SW co-design, and is a classic combinatorial optimisation problem as well, has been proven to be the NP-complete. For a given task, hardware with different areas may provide different execution speeds due to the potential of parallel execution in its implementation. Thus, one task may have multiple-choice in hardware implementation according to the available hardware areas. Existing HW/SW partitioning approaches usually only consider a single hardware implementation manner, but overlook the implementation means with multiple-choice. For the HW/SW partitioning problem with multiple-choice, in this paper we present the solutions with feasibility by using simulated annealing algorithm and genetic algorithm respectively. Moreover, they are compared with tabu search algorithm to find the heuristic algorithm method relatively better for multiple-choice HW/SW partitioning problem. Experimental results show that tabu search is the best algorithm in comparison with other two in terms of the quality of the solution, but the simulated annealing algorithm and genetic algorithm are much faster than tabu search algorithm in the speed of obtaining a better solution.[HQ]
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