> For the complete documentation index, see [llms.txt](https://zeju.gitbook.io/lcm-team/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://zeju.gitbook.io/lcm-team/deepcircuitx/data-for-ppa-prediction.md).

# Data for PPA prediction

We employ logic synthesis tools to transform the RTL code into netlist and record the reports about Power, Performance and Area (PPA). Our dataset could enable predicting PPA metrics based on RTL code. 

#### Example for PPA prediction

Given a complete RTL repositories, train a model to predict the *total dynamic power*, *number of cells* and *maximum path delay* after logic synthesis using a specific standard library. 

{% file src="/files/uFvFL7DB98HVgqjJq7Lm" %}

Ground Truth: 

<table><thead><tr><th width="134">Metric</th><th>Feature</th><th>Number</th></tr></thead><tbody><tr><td>Area</td><td>Number of cells</td><td>4,116</td></tr><tr><td>Power</td><td>Total dynamic power</td><td>23.8842 mW</td></tr><tr><td>Delay</td><td>Maximum path dalay</td><td>19.57 ns</td></tr></tbody></table>