OpenROAD - An Open-Source, Autonomous RTL-GDSII Flow for Chip Design

Mon, 22 Jan 2024 00:00:00 +0000

The OpenROAD project is a non-profit project, originally funded by DARPA with the aim of creating open-source EDA tools; an Autonomous flow from RTL-GDSII that completes < 24 hrs, to lower cost and boost innovation in IC design. This project is now supported by Precision Innovations.

OpenROAD massively scales and supports EWD (Education and Workforce Development) and supports a broad ecosystem making it a vital tool that supports a rapidly growing Semiconductor Industry.

OpenROAD is the fastest onramp to gain knowledge, skills and create pathways for great career opportunities in chip design. You will develop important software and hardware design skills by contributing to these interesting projects. You will also have the opportunity to work with mentors from the OpenROAD project and other industry experts.

We welcome a diverse community of designers, researchers, enthusiasts, software engineers and entrepreneurs to use and contribute to OpenROAD and make a far-reaching impact in the rapidly growing, global Semiconductor Industry.

Create OpenROAD Tutorials and Videos

Topics: Documentation, Tutorials, Videos, VLSI design basics
Skills: Video/audio recording and editing, training and education
Difficulty: Medium
Size: Large (350 hours)
Mentor: Indira Iyer, Vitor Bandeira

Create short videos for training and course curriculum highlighting key features and flows in OpenROAD-flow-scripts.

Improve the OpenROAD AutoTuner Flow and documentation

Topics: OpenROAD-flow-scripts, AutoTuner, Design Exploration
Skills: Knowledge of ML for hyperparameter tuning, Cloud-based computation, Basic VLSI design and tools knowledge, python, C/C++
Difficulty: Medium
Size: Large (350 hours)
Mentor: Vitor Bandeira, Indira Iyer

Test, analyze and enhance the AutoTuner to improve usability, documentation and QoR. The Autotuner is an important tool in the OpenROAD flow - OpenROAD-flow-scripts for Chip design exploration that significantly reduces design time. You will use state-of-the-art ML tools to test the current tool exhaustively for good PPA (performance, power, area) results. You will also update existing documentation to reflect any changes to the tool and flow.

Implement a memory compiler in the OpenROAD Flow

Topics: OpenROAD-flow-scripts, Memory Compiler,
Skills: Basic VLSI design and tools knowledge, python, tcl, C/C++, memory design a plus
Difficulty: Medium
Size: Medium (175 hours)
Mentor: Matt Liberty, Austin Rovinski

Implement a memory compiler as part of the OpenROAD flow to improve the placement and layout efficiency of large, memory-intensive designs. You will start with an existing code base to develop this feature: https://github.com/The-OpenROAD-Project-staging/OpenROAD/tree/dffram This is another option: https://github.com/AUCOHL/DFFRAM Enhance code to support DFFRAM support for the OpenROAD native flow, OpenROAD-flow-scripts.

Integrate a tcl and python linter

Topics: Linting, Workflow
Skills: tcl, python, linting
Difficulty: Easy
Size: Small (90 hours)
Mentor: Vitor Bandeira, Austin Rovinski

Integrate a tcl and python linter for tools in OpenROAD and OpenROAD-flow-scripts to enforce error checking, style and best practices.

LLM assistant for OpenROAD - Create Model Architecture and Prototype

Topics: Large Language Model, Machine Learning, Model Architecture, Model Deployment
Skills: large language model engineering, prompt engineering, fine-tuning
Difficulty: Medium
Size: Medium (175 hours)
Mentor: Indira Iyer, Jack Luar

This project involves the creation of a conversational assistant designed around OpenROAD to answer user queries. You will be working in tandem with members of the OpenROAD team and other researchers to deliver a final deployable prototype. You will focus on the design and implementation of modular LLM architectures. You will be experimenting through different architectures and justifying which approach works the best on our domain-specific data. Open to proposals from all levels of ML practitioners.

LLM assistant for OpenROAD - Data Engineering and testing

Topics: Large Language Model, Machine Learning, Data Engineering, Model Deployment, Testing
Skills: large language model engineering, prompt engineering, fine-tuning
Difficulty: Medium
Size: Medium (175 hours)
Mentor: Indira Iyer, Jack Luar

This project involves the creation of a conversational assistant designed around OpenROAD to answer user queries. You will be working in tandem with members of the OpenROAD team and other researchers to deliver a final deployable prototype. This project will focus on the data engineering portion of the project. This may include: training pipelines specifically tailored for fine-tuning LLM models, data annotation, preprocessing and augmentation. Open to proposals from all levels of ML practitioners.

Create Unit tests for OpenROAD tools

Topics: OpenROAD-flow-scripts, unit testing
Skills: Basic VLSI design and tools knowledge, python, tcl, C/C++, Github
Difficulty: Medium
Size: Medium ( 175 hours)
Mentor: Vitor Bandeira, Indira Iyer

You will build unit tests to test specific features of the OpenROAD tool which will become part of the regression test. Here is an example of a test for UPF support: https://github.com/The-OpenROAD-Project/OpenROAD/blob/master/test/upf/mpd_aes.upf. This is a great way to learn VLSI flow basics and the art of testing them for practical applications.

OpenROAD - An Open-Source, Autonomous RTL-GDSII Flow for VLSI Designs (2023)

Wed, 01 Feb 2023 00:00:00 +0000

The OpenROAD project is a non-profit, DARPA-funded and Google sponsored project committed to creating low-cost and innovative Electronic Design Automation (EDA) tools and flows for IC design. Our mission is to democratize IC design, break down barriers of cost and access and mitigate schedule risk through native and open source innovation and collaboration with ecosystem partners. OpenROAD provides an autonomous, no-human-in-the-loop, 24-hour, RTL-GDSII flow for fast ASIC design exploration, QoR estimation and physical implementation for a range of technologies above 12 nm. We welcome a diverse community of designers, researchers, enthusiasts, software engineers and entrepreneurs to use and contribute to OpenROAD and make a far-reaching impact. OpenROAD has been used in > 600 tapeouts across a range of ASIC applications with a rapidly growing and diverse user community.

Enhance OpenROAD GUI Flow Manager

Topics: GUI, Visualization, User Interfaces
Skills: C++, Qt
Difficulty: Medium
Size: Medium or Large (175 or 350 hours)
Mentor: Matt Liberty, Ethan Mahintorabi

Develop custom features for analysis and visualizations in the [OpenROAD GUI] (https://openroad.readthedocs.io/en/latest/main/src/gui/README.html) to support native and third party flows. These include OpenROAD-flow-scripts, OpenLane and other third-party flows . Create documentation: commands, developer guide notes, tutorials to show GUI usage for supported flows.

Profile and tune OpenROAD flow for Runtime improvements

Topics: OpenROAD-flow-scripts, Flow Manager, Runtime Optimization
Skills: Knowledge about Computational resource optimization, Cloud-based computation, Basic VLSI design and tools knowledge
Difficulty: Medium
Size: Medium or Large (175 or 350 hours)
Mentor: Matt Liberty, Ethan Mahintorabi

Test, analyze and develop verifiable and re-producible strategies to improve run times in OpenROAD-flow-scripts. These include optimizations of computational resources over the cloud, tuning of algorithmic and design flow parameters. Create test plans using existing or new designs to show runtime improvements.

Update OpenROAD Documentation and Tutorials

Topics: Documentation, Tutorials, VLSI design basics
Skills: Knowledge of EDA tools, basics of VLSI design flow, tcl, shell scripts, Documentation, Markdown
Difficulty: Medium
Size: Medium or Large (175 or 350 hours)
Mentor: Indira Iyer, Vitor Bandeira
Contributor(s): Jack Luar

Review and update missing documentation and tutorials in OpenROAD-flow-scripts for existing and new features. Here is an example Tutorial link: https://openroad-flow-scripts.readthedocs.io/en/latest/tutorials/FlowTutorial.html for reference.

LEF and Liberty Model Testing

Topics: Testing, LEF, ‘LIB’, VLSI design basics
Skills: Knowledge of EDA tools, basics of VLSI design, lef and lib model abstracts, tcl, shell scripts, Verilog, Layout
Difficulty: Medium
Size: Medium or Large (175 or 350 hours)
Mentor: Matt Liberty

Test the accuracy of generated LIB and LEF models for signoff in OpenROAD-flow-scripts for flat and hierarchical design flows. Build test cases to validate and add to the regression suite.

Indira Iyer | UCSC OSPO