用自然语言快速预测芯片布局的性能与功耗，精度接近后版图分析。
Lorecast: Layout-Aware Performance and Power Forecasting from Natural Language
- 输入英文提示词，直接生成考虑布局的性能功耗估计。
- 误差仅几百分比，比传统方法快得多。
- 适合芯片设计早期评估，无需编写代码。
在芯片设计规划中，对多种设计方案进行可靠的性能与功耗预测至关重要。传统方法依赖系统级模型，准确性不足；或采用试综合方式，耗时且人力密集。本文提出Lorecast新方法，接收英文提示作为输入，可快速生成考虑布局信息的性能与功耗估算。该方法无需HDL代码编写与综合流程，兼具高效与易用性。实验表明，Lorecast的预测结果与后版图分析相比误差仅几个百分点，同时显著缩短交付周期。
原文摘要 · Abstract (English)
In chip design planning, obtaining reliable performance and power forecasts for various design options is of critical importance. Traditionally, this involves using system-level models, which often lack accuracy, or trial synthesis, which is both labor-intensive and time-consuming. We introduce a new methodology, called Lorecast, which accepts English prompts as input to rapidly generate layout-aware performance and power estimates. This approach bypasses the need for HDL code development and synthesis, making it both fast and user-friendly. Experimental results demonstrate that Lorecast achieves accuracy within a few percent of error compared to post-layout analysis, while significantly reducing turnaround time.
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