The University of Rhode Island, led by Prof. Yeonho Jeong, proposes developing hardware-accelerated machine learning (ML) techniques for electronic design automation (EDA) to advance Integrated Power Electronics Building Block (iPEBB) designs for naval applications.
Key Highlights:
- Innovative Technology: Leverage FPGA-based simulation and ML models to accelerate circuit design by 500x.
- AI-Driven Design: Implement reinforcement learning to optimize power electronics configurations.
- Real-World Testing: Validate designs with prototypes and performance assessments.
Impact and Value:
- For Industry & Leaders: Supports advanced naval power systems and shipboard innovations.
- For Students: Provides opportunities to work on AI, ML, and power electronics design projects.
- For the Nation: Strengthens U.S. naval technological superiority through cutting-edge EDA solutions.
This initiative project combines AI, ML, and high-performance hardware design to drive innovation in naval power systems and cultivate future STEM leaders.
Funding Source: Office of Naval Research (ONR)
Amount: $500,000.68
PI: Yeonho Jeong
Funding Period: August 1, 2024 – July 31, 2029