Glayout

A PDK-agnostic layout automation framework for analog circuit design.

Overview

Glayout is a powerful layout automation tool that generates DRC-clean circuit layouts for any technology implementing the Glayout framework. It is implemented as an easy-to-install Python package with all dependencies available on PyPI.

Key features:

• PDK-agnostic layout generation
• Support for multiple technology nodes (sky130, gf180)
• DRC-clean layout generation
• Natural language processing for circuit design
• Integration with Klayout for visualization and verification

Installation

Basic Installation

pip install .

Development Installation

git clone https://github.com/your-username/glayout.git
cd glayout
pip install -e ".[dev]"

ML Features Installation

pip install -e ".[ml]"

Quick Start

from glayout import sky130, gf180, nmos ,pmos,via_stack

# Generate a via stack
#met2 is the bottom layer. met3 is the top layer.
via = via_stack(sky130, "met2", "met3", centered=True) 

# Generate a transistor
transistor = nmos(sky130, width=1.0, length=0.15, fingers=2)

# Write to GDS
via.write_gds("via.gds")
transistor.write_gds("transistor.gds")

Documentation

For detailed documentation, please visit our documentation site.

Features

PDK Agnostic Layout

• Generic layer mapping
• Technology-independent design rules
• Support for multiple PDKs (sky130, gf180)

Circuit Generators

• Via stack generation
• Transistor generation (NMOS/PMOS)
• Guard ring generation
• And more...

Natural Language Processing

• Convert natural language descriptions to layouts
• Support for standard components
• Custom component definitions

Supported Open Source PDKs

• SkyWater SKY-130A
• GlobalFoundries GF-180mcuD

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use Glayout in your research, please cite our papers:

@article{hammoud2024human,
  title={Human Language to Analog Layout Using Glayout Layout Automation Framework},
  author={Hammoud, A. and Goyal, C. and Pathen, S. and Dai, A. and Li, A. and Kielian, G. and Saligane, M.},
  journal={Accepted at MLCAD},
  year={2024}
}

@article{hammoud2024reinforcement,
  title={Reinforcement Learning-Enhanced Cloud-Based Open Source Analog Circuit Generator for Standard and Cryogenic Temperatures in 130-nm and 180-nm OpenPDKs},
  author={Hammoud, A. and Li, A. and Tripathi, A. and Tian, W. and Khandeparkar, H. and Wans, R. and Kielian, G. and Murmann, B. and Sylvester, D. and Saligane, M.},
  journal={Accepted at ICCAD},
  year={2024}
}

Contact

For questions and support, please contact:

• Email: mehdi_saligane@brown.edu