Machine Learning Applications in EDA for Chiplet Reliability
Learn how AI is transforming chip design and enhancing semiconductor reliability. In this webinar, leading researchers share insights into cutting-edge advancements in the field:
đš Dr. George Floros
đš Dr. Tahani Aladwani
đš Dr. Yixian Shen
đš Dr. Olympia Axelou
This webinar was part of COIN3D, a Horizon Europe Twinning project, co-funded by the European Union. It was organized in collaboration with:
đī¸ University of Thessaly
đī¸ University of Amsterdam
đī¸ University of Bremen
đī¸ University of Glasgow
Related Chiplet
- FlexGen Multi-Die Smart Network-on-Chip (NoC) IP
- Ncore Multi-Die Interconnect IP
- Integrated voltage regulator (IVR) chiplet
- High-performance connectivity chiplets
- eFPGA Chiplet
Related Videos
- Custom Tool Development Strategies for Chiplet Reliability
- Rethinking chip(let) design for next generation ADAS applications
- AI-Driven Thermal Prediction for Enhanced Reliability in 3D HBM Chiplets
- A Physics-Informed Neural Network Surrogate for Runtime PDN and Dynamic Droop Prediction in 2.5-D Chiplet Integration
Latest Videos
- Accelerating Chiplet SoC Development with Standards-Based Frameworks and Automated Design Flows
- Qualcomm's Tony Pialis on Dragonfly and the Data Movement Wall
- From silos to system: Sujit Sharan on the cultural and technical shift 3D IC demands
- Advancing 3DIC Technologies to Propel AI Innovations
- Building Real Confidence in Chiplet Stacks with Evelyn Landman of proteanTecs