Power Virus Generation Using Behavioral Models of Circuits
Power Virus Generation Using Behavioral Models of Circuits
复制标题
使用电路行为模型生成电源病毒
DOI：
10.1109/vts.2007.49
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
V. Vedula
中科院分区：
文献类型：
--
作者：
K. Najeeb;V. Vardhan;R. Konda;S. Kumar;S. Hari;V. Kamakoti;V. Vedula
CMOS电路中峰值功率估计的问题对于分析极端条件下电路的可靠性和性能至关重要。消散的动态功率与电路中切换活动（更改状态）的开关活动（更改状态）直接成正比。功率病毒问题涉及查找导致电路中最大动态功率耗散（最大切换）的输入向量。由于功率病毒问题是NP完整的，因此随着设计尺寸的增加，栅极级技术的扩展性较小，并且产生较少的最佳矢量。在本文中，提出了使用数字电路行为模型生成功率病毒的方法。提出的技术将给定的行为模型自动转换为整数（单词级）约束模型，并采用整数约束求解器来生成所需的功率病毒向量。在ISCAS行为水平基准电路和标准DLX处理器模型上试验所提出的技术表明，上述技术是快速的，并且比已知的栅极级技术产生更高的质量结果。有趣的是，本文试图生成一个装配程序，该程序在给定的DLX处理器模型上导致最大动态功率耗散。据我们所知，提出的技术是第一个报道使用行为水平模型来考虑发电病毒的人。
The problem of peak power estimation in CMOS circuits is essential for analyzing the reliability and performance of circuits at extreme conditions. The dynamic power dissipated is directly proportional to the switching activity (number of gate outputs that toggles (changes state)) in the circuit. The power virus problem involves finding input vectors that cause maximum dynamic power dissipation (maximum toggles) in circuits. As the power virus problem is NP-complete the gate-level techniques are less scalable with increasing design size and produce less optimal vectors. In this paper, an approach for power virus generation using behavioral models of digital circuits is presented. The proposed technique converts the given behavioral model automatically to an integer (word-level) constraint model and employs an integer constraint solver to generate the required power virus vectors. Experimenting the proposed technique on ISCAS behavioral level benchmark circuits and the standard DLX processor model show that the above technique is fast and yields higher-quality results than the known gate-level techniques. Interestingly, the paper attempts to generate an assembly program that cause the maximum dynamic power dissipation on the given DLX processor model. To the best of our knowledge the proposed technique is the first reported that considers power virus generation using behavioral level models.