重定时下统计关键序列路径的高效计算

M. Ekpanyapong, Xin Zhao, S. Lim
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引用次数: 0

摘要

本文提出了一种基于统计时序的时序分析算法。目标是计算时序图中节点的时序松弛分布,并识别重定时下的统计关键路径,即重定时后具有高概率成为时序关键的路径。SRTA使设计人员能够在这些路径上执行电路优化,以减少如果电路作为后处理重新计时,它们成为时间瓶颈的可能性。我们对静态时序分析(=STA)、统计时序分析(=SSTA)、基于时序分析(=RTA)和基于统计时序分析(= SRTA)进行了比较。结果表明,基于SRTA的布局优化获得了最佳的性能效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Efficient Computation of Statistically Critical Sequential Paths Under Retiming
In this paper we present the statistical retiming-based timing analysis (SRTA) algorithm. The goal is to compute the timing slack distribution for the nodes in the timing graph and identify the statistically critical paths under retiming, which are the paths with a high probability of becoming timing-critical after retiming. SRTA enables the designers to perform circuit optimization on these paths to reduce the probability of them becoming timing bottleneck if the circuit is retimed as a post-process. We provide a comparison among static timing analysis (=STA), statistical timing analysis (=SSTA), retiming-based timing analysis (=RTA), and our statistical retiming-based timing analysis (SRTA). Our results show that the placement optimization based on SRTA achieves the best performance results.
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