Design automation tools and libraries for low power digital design

Mohammad Rahman, R. Afonso, Hiran Tennakoon, C. Sechen
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引用次数: 19

Abstract

Assuming arbitrary (continuous cell sizes) we have achieved global minimization of the total transistor sizes needed to achieve a delay goal, thus minimizing dynamic power (and reducing leakage power). We then developed a feasible branch-and-bound algorithm that maps the continuous sizes to the discrete sizes available in the standard cell library. Results show that a well-designed library gives results close to the optimal continuous size results. We developed a new approach to threshold voltage selection, among options available in a cell library. This algorithm is applied after optimal gate size selection, and raises threshold voltages as much as possible while strictly maintaining the delay goal. In addition, we identified the optimal set of (just 8) combinational functions in a physical cell library. These constitute the most power efficient cells needed to implement combinational logic. On the other hand, the synthesis library is much more complex, consisting of cells that are combinations of the physical library cells. This is advantageous since the constituent cells (of a more complex synthesis cell) are placed next to each other in the layout, ensuring minimal wire length between them. Since wire delay is a significant portion of total path delay for contemporary circuits, having complex cells in synthesis is important. But, for power efficiency, the physical cells must be rather simple, with no more than two transistors in series for any cell. The entire cell size and threshold voltage selection flow is efficient, with an ability to handle multi-million-gate commercial designs. After using state-of-the-art commercial synthesis, the application of our design automation tools and library results in a dynamic power reduction of 25–35% and leakage power reduction by 50–70% for large logic blocks.
为低功耗数字设计设计自动化工具和库
假设任意(连续的电池尺寸),我们已经实现了实现延迟目标所需的总晶体管尺寸的全局最小化,从而最小化动态功率(并减少泄漏功率)。然后,我们开发了一种可行的分支定界算法,将连续大小映射到标准细胞库中可用的离散大小。结果表明,设计良好的库可以得到接近最优连续尺寸的结果。我们开发了一种新的阈值电压选择方法,在单元库中可用的选项中。该算法在优化栅极尺寸选择后,在严格保持延迟目标的前提下,尽可能提高阈值电压。此外,我们还确定了物理细胞库中的最佳组合函数集(仅8个)。这些构成了实现组合逻辑所需的最高效的电池。另一方面,合成库要复杂得多,它由物理库细胞组合而成的细胞组成。这是有利的,因为组成单元(更复杂的合成单元)在布局中彼此相邻放置,确保它们之间的导线长度最小。由于导线延迟是当代电路总路径延迟的重要组成部分,因此在合成中使用复杂的细胞是很重要的。但是,为了提高功率效率,物理电池必须相当简单,任何电池串联的晶体管不得超过两个。整个电池尺寸和阈值电压选择流程是有效的,具有处理数百万栅极商业设计的能力。在使用最先进的商业合成后,我们的设计自动化工具和库的应用使大型逻辑块的动态功率降低了25-35%,泄漏功率降低了50-70%。
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