Presentation
AI-Assisted Design Optimization for Extensive Design Spaces: Handling 260,000+ Combinations
DescriptionThis presentation discusses how an AI-assisted design optimization methodology provides a verified optimal solution for two circuits: metal-option switches and charge pumps. By exploring the entire design space, up to 260,000 design combinations in this case, it results in a faster design cycle, improved capacity, and reduced CPU time.
Micron uses metal-layer switches in its circuits for adjustment to changes. These switches need tuning multiple times during a product design cycle; they might also require adjustment post-tapeout if the process varies, causing poor circuit performance. On the other hand, charge pumps are widely used in memory design for converting a supply voltage to a higher or lower value.
The traditional tuning methods of the above-mentioned circuits involve an iterative manual process to explore as many of the design combinations as possible. This process is time-consuming and may lead to sub-optimal solutions.
This presentation covers the motivation behind the work, the methodology used, and the results obtained by the design team. We also discuss the algorithm behind the AI-powered solution that helped achieve these results.
Micron uses metal-layer switches in its circuits for adjustment to changes. These switches need tuning multiple times during a product design cycle; they might also require adjustment post-tapeout if the process varies, causing poor circuit performance. On the other hand, charge pumps are widely used in memory design for converting a supply voltage to a higher or lower value.
The traditional tuning methods of the above-mentioned circuits involve an iterative manual process to explore as many of the design combinations as possible. This process is time-consuming and may lead to sub-optimal solutions.
This presentation covers the motivation behind the work, the methodology used, and the results obtained by the design team. We also discuss the algorithm behind the AI-powered solution that helped achieve these results.
Event Type
Engineering Track Poster
TimeMonday, June 245:00pm - 6:00pm PDT
LocationLevel 2 Exhibit Hall
Back-End Design
Embedded Systems
Front-End Design
IP