AgenticTCAD: LLM-Driven Device Design Optimization
Analysis
This paper addresses the challenge of automating TCAD simulation and device optimization, a crucial aspect of modern semiconductor design. The use of a multi-agent framework driven by a domain-specific language model is a novel approach. The creation of an open-source TCAD dataset is a valuable contribution, potentially benefiting the broader research community. The validation on a 2 nm NS-FET and the comparison to human expert performance highlights the practical impact and efficiency gains of the proposed method.
Key Takeaways
- •Proposes AgenticTCAD, a multi-agent framework for automated TCAD code generation and device optimization.
- •Utilizes a domain-specific language model fine-tuned on an open-source TCAD dataset.
- •Demonstrates significant efficiency gains compared to human experts in device design.
- •Addresses the scarcity of open-source resources in TCAD simulation.
Reference
“AgenticTCAD achieves the International Roadmap for Devices and Systems (IRDS)-2024 device specifications within 4.2 hours, whereas human experts required 7.1 days with commercial tools.”