| 摘要 |
A persistence-driven optimization technique is provided in which nets can be ranked based on unpredictability and likely quality of result impact. The top nets in that ranking can be routed and their parasitics extracted. A timing graph can be back-annotated with route-based delays and parasitics for the selected nets. At this point, synthesis can be run using actual route-based delays and parasitics for the selected nets, with their routes being updated incrementally as needed. In one embodiment, the nets can be re-ranked after synthesis. Finally, these routes can be preserved across the subsequent global routing of the remaining nets.
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