Presentation
User Definable Custom Primitives in 3DIC AI-Driven STCO: Case Study on Power Grid Optimization for IR Enhancement
DescriptionIn AI-driven design optimization EDA flows, there is usually a pre-defined list of primitives, which are options or parameters, that the flow can experiment on. By fine-tuning primitive values using AI-driven algorithms and analysis, EDA flows aim to produce optimal PPA (performance, power, and area) results with little user guidance. The pre-defined primitive list, however, is not likely to be completely comprehensive, and users may request for additional primitives to further improve PPA. Adding new primitives to EDA flows can take significant amount of time due to software development and qualification timelines. In this work, we propose a novel methodology to allow users to add customized primitives into existing AI-assisted EDA flows. We demonstrate a case study on 3DIC power grid optimization to showcase this capability. Power grids are usually product specific, and therefore prevents EDA vendors from pre-defining primitives related to power grid even for the same process technology. By using this methodology, users can instantaneously add or change customized primitives to expand capabilities in AI-driven optimization flows by exploring additional design/flow parameters not existed before, and thus opening new realms of possibilities for PPA improvements with fast turn-around-time.
Event Type
Engineering Poster
TimeTuesday, July 285:00pm - 6:00pm PDT
LocationDAC Pavilion, Exhibit Floor