一种基于离散Hopfield神经网络的SoC嵌入式
操作系统软/硬件划分方法
A Discrete Hopfield Neural Network Approach for Hardware-software Partitioning of Embedded Operating System in the SoC
作者：郭兵(四川大学 计算机学院,四川 成都 610065)；沈艳(电子科技大学 机械电子工程学院，四川 成都 610054)；王典辉(La Trobe大学 计算机系,墨尔本 VIC 3086, 澳大利亚)
Author：(School of Computer, Sichuan Univ., Chengdu 610065, China)；(School of Mechatronics Eng., Univ. of Electronic Sci. & Technol. of China, Chengdu 610054,China)；(Dept. of Computer Sci. & Eng., La Trobe Univ., Melbourne, VIC 3086, Australia)
收稿日期：2006-01-04 年卷（期）页码：2006,38(5):122-127
期刊名称：工程科学与技术
Journal Name：Advanced Engineering Sciences
关键字：Hopfield神经网络；软/硬件划分；嵌入式操作系统；SoC；SoC-EOS划分
Key words：Hopfield neural network; hardware-software partitioning; embedded operating system; SoC; SoC-EOS partitioning
基金项目：国家自然科学基金资助项目（60572026）
中文摘要
SoC（System-on-a-Chip ）系统芯片的嵌入式操作系统(Embedded Operating System)软/硬件自动划分（SoC EOS划分）是一个NP完全问题，也是SoC软/硬件协同设计的一个关键步骤，它决定了SoC-EOS功能的软/硬件实现，其划分结果直接影响到SoC产品的开发效率和质量。引入了SoC-EOS划分问题的一个新模型，这有助于理解SoC EOS划分问题的本质。提出了一种基于离散Hopfield神经网络的SoC-EOS划分方法，重新定义了神经网络的能量函数、运行方程和相关系数。最后，对该方法进行了仿真实验，并同遗传算法和蚂蚁算法进行了性能比较。实验结果表明，提出的神经网络方法是可行的和有效的。
英文摘要
The hardware-software automatic partitioning of embedded operating system in the SoC (SoC-EOS partitioning) is a NP-complete problem, and a crucial step in the hardware-software co-design of SoC. It determines the hardware-software implementation of SoC-EOS, and its result directly influences the development efficiency and quality of SoC products.A new model for SoC-EOS partitioning was introduced, which can help on understanding the essence of the SoC-EOS partitioning.A discrete Hopfield neural network approach for implementing the SoC-EOS partitioning was proposed, where a novel energy function, operating equation and coefficients of the neural network are redefined. Then simulations were carried out with comparisons to the genetic algorithm and ant algorithm in the performance. Experimental results demonstrated the feasibility and effectiveness of the proposed method.
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