发表机构
Fudan University（复旦大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出BBYT方法，将重写决策候选编译为零延迟镜像以减少时序评估时间，在多组实验中实现时间减少，且与穷举时序选择结果一致。
AI 中文摘要
带标准延迟格式（SDF）标注的开关仿真可区分功能等价重写中与延迟相关的活动，但评估每个候选会重复执行时序、编译和重放过程。零延迟代理可消除时序评估，但逐个候选生成代理的成本可能超过其节省的时序工作。我们提出先批量后定时（BBYT）方法，将一次重写决策的所有候选编译为一个范围限定的零延迟镜像，要么选择一个区分度良好的代理候选，要么调用未改变的时序链。在12个平衡保留序列上，BBYT使完整候选选择时间平均减少18.05%；设计级别的减少量为5.84%和30.25%，两个置信区间均大于0。在平衡的8192个转换的C6288工作负载上，BBYT比逐个候选启动代理的相同门电路快9.24%。在5个工作负载语料库中，BBYT消除了32.52%的时序候选评估，且在所有250个评估决策上与穷举时序选择结果一致。对于按需时序感知重写选择，代理执行和保真度延续应使用相同的决策范围。
英文摘要
Standard Delay Format (SDF)-annotated switching simulation distinguishes delay-dependent activity among functionally equivalent rewrites, but evaluating every candidate repeats timing, compilation, and replay. A zero-delay proxy can remove timed evaluations, but generating that proxy candidate by candidate can cost more than the timed work it saves. We present Batch Before You Time (BBYT), which compiles all candidates of one rewrite decision into one scoped zero-delay image and either commits a well-separated proxy winner or invokes the unchanged timed chain. Across 12 counterbalanced holdout sequences, BBYT reduces complete candidate-selection time by 18.05% on average; the design-level reductions are 5.84% and 30.25%, with both confidence intervals above zero. On a counterbalanced 8,192-transition C6288 workload, BBYT is 9.24% faster than the same gate executed with candidate-wise proxy launches. In the five-workload corpus, BBYT removes 32.52% of timed candidate evaluations and matches exhaustive timed selection on all 250 evaluated decisions. For on-demand timing-aware rewrite selection, proxy execution and fidelity continuation should use the same decision scope.
Comments6 pages, 3 figures
