Presentation
Deterministic, Solver‑Accurate Physics Intelligence for Chips‑to‑Systems Design: What Breaks, What Validates, What Automates
DescriptionAs chiplet architectures, 3D integration, and HBM‑class systems push thermal‑mechanical‑electrical coupling into the critical path, engineering teams are discovering that traditional simulation workflows—built around manual setup, sparse sampling, and human‑driven iteration—cannot scale to manufacturing‑resolution design. In this regime, nondeterminism, approximation, and workflow variability become failure modes rather than accelerants.
This session examines what it takes to make physics‑based AI viable for production engineering workflows, where deterministic execution, solver‑accurate validation, and reproducible physics reasoning are essential. We will explore what breaks when probabilistic or approximate methods are applied to high‑stakes physical design, the technical and operational criteria required for trustable results, and which elements of chips‑to‑systems workflows can be automated once physics reasoning operates continuously at machine scale. Drawing on semiconductor, advanced packaging, thermal, and multiphysics domains, a panel of industry and academic experts will discuss how deterministic, physics‑grounded AI enables broader design exploration within real development timelines.
This session examines what it takes to make physics‑based AI viable for production engineering workflows, where deterministic execution, solver‑accurate validation, and reproducible physics reasoning are essential. We will explore what breaks when probabilistic or approximate methods are applied to high‑stakes physical design, the technical and operational criteria required for trustable results, and which elements of chips‑to‑systems workflows can be automated once physics reasoning operates continuously at machine scale. Drawing on semiconductor, advanced packaging, thermal, and multiphysics domains, a panel of industry and academic experts will discuss how deterministic, physics‑grounded AI enables broader design exploration within real development timelines.
Organizer
Moderator
Event Type
Engineering Special Session
TimeMonday, July 271:30pm - 3:00pm PDT
LocationSeaside RM 7
AI
Chiplet
Design
EDA
Systems