data/markdown/OR_docs/OR_readme.md

# Welcome to OpenROAD's documentation!

The OpenROAD ("Foundations and Realization of Open, Accessible Design")
project was launched in June 2018 within the DARPA IDEA program. OpenROAD
aims to bring down the barriers of cost, expertise and unpredictability that
currently block designers' access to hardware implementation in advanced
technologies. The project team (Qualcomm, Arm and multiple universities and
partners, led by UC San Diego) is developing a fully autonomous, open-source
tool chain for digital SoC layout generation, focusing on
the RTL-to-GDSII phase of system-on-chip design. Thus,
OpenROAD holistically attacks the multiple facets of today's design cost
crisis: engineering resources, design tool licenses, project schedule,
and risk.

The IDEA program targets no-human-in-loop (NHIL) design, with 24-hour
turnaround time and zero loss of power-performance-area (PPA) design quality.

The NHIL target requires tools to adapt and auto-tune successfully to flow
completion, without (or, with minimal) human intervention. Machine
intelligence augments human expertise through efficient modeling and
prediction of flow and optimization outcomes throughout the synthesis, placement
and routing process. This is complemented by development of metrics
and machine learning infrastructure.

The 24-hour runtime target implies that problems must be strategically
decomposed throughout the design process, with clustered and partitioned
subproblems being solved and recomposed through intelligent distribution
and management of computational resources. This ensures that the NHIL design
optimization is performed within its available `[threads * hours]` "box" of
resources. Decomposition that enables parallel and distributed search over
cloud resources incurs a quality-of-results loss, but this is subsequently
recovered through improved flow predictability and enhanced optimization.

For a technical description of the OpenROAD flow, please refer to our DAC-2019 paper:
[Toward an Open-Source Digital Flow: First Learnings from the OpenROAD Project](https://vlsicad.ucsd.edu/Publications/Conferences/371/c371.pdf).
The paper is also available from [ACM Digital Library](https://dl.acm.org/doi/10.1145/3316781.3326334).
Other publications and presentations are
linked [here](https://theopenroadproject.org/publications/).

## Documentation

The OpenROAD Project has two releases:

- Application ([github](https://github.com/The-OpenROAD-Project/OpenROAD)) ([docs](main/README.md)): The application is a standalone binary for digital place and route that can be used by any other RTL-GDSII flow controller.
- Flow ([github](https://github.com/The-OpenROAD-Project/OpenROAD-flow-scripts)) ([docs](https://openroad-flow-scripts.readthedocs.io/en/latest/)): This is the native OpenROAD flow that consists of a set of integrated scripts for an autonomous RTL-GDSII flow using OpenROAD and other open-source tools.

## Code of conduct

Please read our code of conduct [here](main/CODE_OF_CONDUCT.md).

## How to contribute

If you are willing to **contribute**, see the
[Getting Involved](contrib/GettingInvolved.md) section.

If you are a **developer** with EDA background, learn more about how you
can use OpenROAD as the infrastructure for your tools in the
[Developer Guide](contrib/DeveloperGuide.md) section.

OpenROAD uses Git for version control and contributions. 
Get familiarised with a quickstart tutorial to contribution [here](contrib/GitGuide.md).

## How to get in touch

We maintain the following channels for communication:

-   Project homepage and news: <https://theopenroadproject.org>
-   Twitter: <https://twitter.com/OpenROAD_EDA>
-   Issues and bugs:
    -   OpenROAD: <https://github.com/The-OpenROAD-Project/OpenROAD/issues>
-   Discussions:
    -   OpenROAD: <https://github.com/The-OpenROAD-Project/OpenROAD/discussions>
-   Inquiries: openroad@ucsd.edu

See also our [FAQs](user/FAQS.md).

## Site Map

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