低功率行为综合

Guan-jun Wang, Ying Zhao
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引用次数: 0

摘要

本文提出了一个行为综合过程中降低功率的框架。定义了一个新的参数,称为循环功率积(CPP),它将功率特性捕获为归一化平均周期功率的等加权和。为了最小化该参数,使用多个电源电压和动态频率时钟,从而减少能量和瞬态功率。循环微分功率可以建模为与平均功率的平均偏差,也可以建模为周期到周期的功率梯度。切换活动信息通过行为模拟得到。在此基础上,提出了一种新的数据路径调度算法,该算法通过最小化调度过程中的CPP参数来实现功率和能量的最小化。可用功能单元的类型和数量成为调度器的资源约束集。实验结果表明,以CPP最小为目标函数而不是以常规能量或平均功率为目标函数的调度程序可以显著降低功率和能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Low Power Behavioral Synthesis
In this paper, a framework for reducing power during behavioral synthesis is proposed. A new parameter called Cycle Power Product (CPP) is defined which captures the power characteristics as an equally weighted sum of normalized mean cycle power. To minimize this parameter uses multiple supply voltages and dynamic frequency clocking and results in reduction of both energy and transient power. The cycle differential power can be modeled either as the mean deviation from the average power or as the cycle-to-cycle power gradient. The switching activity information is obtained from behavioral simulations. Based on the above we develop a new datapath scheduling algorithm which attempts at power and energy minimization by minimizing the CPP parameter during the scheduling process. The type and number of functional units available becomes the set of resource constraints for the scheduler. Experimental results indicate that the scheduler that minimizes CPP instead of conventional energy or average power as objective function could achieve significant reductions in power and energy.
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