6 papers · 1 filter
PCB-QA: Evaluating LLMs over the First Printed Circuit Board Design Question-Answer Dataset
Sahana Srinivasan, Benjamin Tan, Benjamin Turnbull +1
Large Language Models (LLMs) have demonstrated capabilities in electronic design automation (EDA) for integrated circuits. However, their applications in printed circuit board (PCB…
Surveying GenAI-based Automation in Printed Circuit Board Design and Test
Sahana Srinivasan, Benjamin Turnbull, Hammond Pearce
Generative artificial intelligence (GenAI) is increasingly used for applications in the hardware and software domains. It purports to reduce the manual effort involved in the devel…
Towards LLM-based Root Cause Analysis of Hardware Design Failures
Siyu Qiu, Muzhi Wang, Raheel Afsharmazayejani +3
With advances in large language models (LLMs), new opportunities have emerged to develop tools that support the digital hardware design process. In this work, we explore how LLMs c…
Automatically Improving LLM-based Verilog Generation using EDA Tool Feedback
Jason Blocklove, Shailja Thakur, Benjamin Tan +3
Traditionally, digital hardware designs are written in the Verilog hardware description language (HDL) and debugged manually by engineers. This can be time-consuming and error-pron…
Evaluating LLMs for Hardware Design and Test
Jason Blocklove, Siddharth Garg, Ramesh Karri +1
Large Language Models (LLMs) have demonstrated capabilities for producing code in Hardware Description Languages (HDLs). However, most of the focus remains on their abilities to wr…
LLM-aided explanations of EDA synthesis errors
Siyu Qiu, Benjamin Tan, Hammond Pearce
Training new engineers in digital design is a challenge, particularly when it comes to teaching the complex electronic design automation (EDA) tooling used in this domain. Learners…