OpenROAD GSoC 2025

content/authors/luarss/_index.md

@@ -10,14 +10,12 @@ authors:
 superuser: false
 
 # Role/position
-role: "Student at National University of Singapore"
+role: "Individual Contributor"
 
 # Organizations/Affiliations
 organizations:
-  - name: School of Computing
-    url: "https://www.comp.nus.edu.sg/"
-  - name: National University of Singapore
-    url: "https://nus.edu.sg/"
+  - name: Precision Innovations
+    url: https://precisioninno.com/
 
 
 # Short bio (displayed in user profile at end of posts)
@@ -30,7 +28,7 @@ bio:
 social:
 - icon: envelope
   icon_pack: fas
-  link: mailto:espsluar@gmail.com
+  link: mailto:jluar@precisioninno.com
 - icon: linkedin
   icon_pack: fab
   link: https://www.linkedin.com/in/song-luar
@@ -45,4 +43,6 @@ user_groups:
   - 2023 Contributors
   - University of California Mentors
 ---
-Jack is a Masters graduate from the National University of Singapore. Key interests are in open-source Electronic Design Automation (EDA) and applying AI for Very Large Scale Integration (VLSI) design optimisation. 
+Jack is a Masters graduate from the National University of Singapore. Key interests are in open-source Electronic Design Automation (EDA) and applying AI for Very Large Scale Integration (VLSI) design optimisation.
+
+In GSoC 2024, he mentored two students and shipped the [ORAssistant](https://github.com/The-OpenROAD-Project/ORAssistant) project, a conversational chatbot meant to answer queries about OpenROAD and the OpenROAD-flow-scripts suite.

content/project/osre25/openroad/openroad/index.md

@@ -0,0 +1,35 @@
+---
+title: "OpenROAD - An Open-Source, Autonomous RTL-GDSII Flow for Chip Design"
+authors: [luarss]
+author_notes: ["Individual Contributor at Precision Innovations"]
+tags: ["osre24", "ucsd", "uc", "chip design", "asicdesign", "llm", "ml", "ai"]
+date: 2025-01-19
+---
+
+The [OpenROAD](https://theopenroadproject.org) 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](precisioninno.com).
+
+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.
+
+### ORAssistant - LLM Data Engineering and Testing
+
+  * **Topics**: `Large Language Model`, `Machine Learning`, `Data Engineering`, `Model Deployment`, `Testing`
+  * **Skills**: large language model engineering, database, evaluation, CI/CD, open-source or related software development
+  * **Difficulty**: Medium
+  * **Size**: Medium (175 hours)
+  * **Mentor**: Jack Luar
+
+This project is aimed at enhancing robustness and accuracy for OR Assistant. the conversational assistant for OpenROAD through comprehensive testing and evaluation. You will work with members of the OpenROAD team and other researchers to enhance the existing dataset to cover a wide range of use cases to deliver accurate responses more efficiently. This project will focus on data engineering and benchmarking and you will collaborate on a project on the LLM model engineering. Tasks include: creating evaluation pipelines, building databases to gather feedback, and improving CI/CD (non-exhaustive), writing documentation. You will gain valuable experience and skills in understanding chip design flows and applications. Open to proposals from all levels of ML practitioners.
+
+### ORAssistant - LLM Model Engineering
+
+  * **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**: Jack Luar
+
+This project is aimed at enhancing robustness and accuracy for OR Assistant, the conversational assistant for OpenROAD through enhanced model architectures. You will work with members of the OpenROAD team and other researchers to explore alternate architectures beyond the existing RAG-based implementation. This project will focus on improving reliability and accuracy of the existing model architecture. You will collaborate on a tandem project on data engineering for OR assistant. Tasks include: reviewing and understanding the state-of-the-art in retrieval augmented generation, implementing best practices, caching prompts, improving relevance and accuracy metrics (non-exhaustive), writing documentation.  You will gain valuable experience and skills in understanding chip design flows and applications. Open to proposals from all levels of ML practitioners.