升降参数下的性能优化

R. Murgai
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引用次数: 18

摘要

通常情况下,诸如引脚到引脚固有延迟、负载相关系数和输入引脚电容等单元参数对于上升和下降信号具有不同的值。然而,性能优化算法为每个参数假设一个值。没有研究单独的上升和下降值对优化复杂性的影响。我们迈出了理解这种影响的第一步。我们选择两个具有多项式时间复杂度的问题,假设每个单元格参数只有一个值。第一个问题是在一个固定拓扑网络上的缓冲区插入,以最大化在网络源处所需的时间。第二个是门调整问题(以及更一般的技术映射问题),以便在最简单的,负载无关的延迟模型下最小化电路延迟。我们证明了在单独的上升和下降参数下,这两个问题都是np完全的。据我们所知,这是第一个显示上升和下降参数对性能优化问题复杂性影响的结果。然后,我们解决了设计一个好的实用的局部扇出优化算法的重要问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance optimization under rise and fall parameters
Typically, cell parameters such as the pin-to-pin intrinsic delays, load-dependent coefficients, and input pin capacitances have different values for rising and falling signals. The performance optimization algorithms, however, assume a single value for each parameter. No work has been done to study the impact of separate rise and fall values on the complexity of optimization. We take the first step towards understanding this impact. We pick two problems that have polynomial-time complexities if a single value for each cell parameter is assumed. The first problem is that of buffer insertion on a fixed topology net to maximize the required time at the source of the net. The second is the gate resizing problem (and the more general technology mapping problem) for minimizing the circuit delay under the simplest, load-independent delay model. We show that under separate rise and fall parameters, both these problems become NP-complete. To the best of our knowledge, this is the first such result showing the effect of rise and fall parameters on the complexity of performance optimization problems. We then address the important question of devising a good practical algorithm for local fanout optimization.
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