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From RTL to Prompt Coding: Empowering the Next Generation of Chip Designers through LLMs

Lukas Krupp, Matthew Venn, Norbert Wehn

TL;DR

Problem: the chip-design field faces a growing talent gap and high-entry barriers for RTL learning. Approach: integrate an LLM-based chat agent into a browser-based Tiny Tapeout workflow to guide non-experts from idea to RTL generation and tapeout. Contributions: first holistic education platform spanning frontend RTL coding and backend tapeout, a VGA-focused learning workflow, and a case study with 18 high-school students demonstrating tapeout-ready designs. Significance: shows that accessible, open-source tooling can broaden participation in chip design and catalyze skill development at earlier education stages.

Abstract

This paper presents an LLM-based learning platform for chip design education, aiming to make chip design accessible to beginners without overwhelming them with technical complexity. It represents the first educational platform that assists learners holistically across both frontend and backend design. The proposed approach integrates an LLM-based chat agent into a browser-based workflow built upon the Tiny Tapeout ecosystem. The workflow guides users from an initial design idea through RTL code generation to a tapeout-ready chip. To evaluate the concept, a case study was conducted with 18 high-school students. Within a 90-minute session they developed eight functional VGA chip designs in a 130 nm technology. Despite having no prior experience in chip design, all groups successfully implemented tapeout-ready projects. The results demonstrate the feasibility and educational impact of LLM-assisted chip design, highlighting its potential to attract and inspire early learners and significantly broaden the target audience for the field.

From RTL to Prompt Coding: Empowering the Next Generation of Chip Designers through LLMs

TL;DR

Problem: the chip-design field faces a growing talent gap and high-entry barriers for RTL learning. Approach: integrate an LLM-based chat agent into a browser-based Tiny Tapeout workflow to guide non-experts from idea to RTL generation and tapeout. Contributions: first holistic education platform spanning frontend RTL coding and backend tapeout, a VGA-focused learning workflow, and a case study with 18 high-school students demonstrating tapeout-ready designs. Significance: shows that accessible, open-source tooling can broaden participation in chip design and catalyze skill development at earlier education stages.

Abstract

This paper presents an LLM-based learning platform for chip design education, aiming to make chip design accessible to beginners without overwhelming them with technical complexity. It represents the first educational platform that assists learners holistically across both frontend and backend design. The proposed approach integrates an LLM-based chat agent into a browser-based workflow built upon the Tiny Tapeout ecosystem. The workflow guides users from an initial design idea through RTL code generation to a tapeout-ready chip. To evaluate the concept, a case study was conducted with 18 high-school students. Within a 90-minute session they developed eight functional VGA chip designs in a 130 nm technology. Despite having no prior experience in chip design, all groups successfully implemented tapeout-ready projects. The results demonstrate the feasibility and educational impact of LLM-assisted chip design, highlighting its potential to attract and inspire early learners and significantly broaden the target audience for the field.
Paper Structure (9 sections, 3 figures, 1 table)

This paper contains 9 sections, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background and Related Work
  3. Methodology
  4. System Overview & Learning Workflow
  5. LLM-based Chat Agent System
  6. Case Study: High-School Student Evaluation
  7. Experimental Setup
  8. Results and Observations
  9. Conclusion and Future Work

Figures (3)

  • Figure 1: Overview of the proposed idea-to-GDSII learning workflow integrating the LLM-based chat agent for the RTL implementation, VGA simulation tool, and GitHub-driven backend flow. The browser-based user interfaces (UIs) and the underlying applications are shown.
  • Figure 2: Overview of the LLM-based chat agent system.
  • Figure 3: Results of the survey on students' background knowledge.