Presentation
AI and Multi‑die: A Reinforcing Cycle
DescriptionThe convergence of AI and multi‑die architectures is reshaping the fundamentals of compute efficiency. Near‑memory and in‑memory processing—enabled by advanced non‑volatile memory technologies—reduces data movement and latency, accelerating AI workloads at their source. Cost‑effective multi‑die integration unlocks scalable performance without escalating silicon expense, fueling innovation from edge devices to hyperscale cloud.
Automotive‑grade AI raises the bar further, requiring multi‑die reliability that meets rigorous functional‑safety demands. Sustainability pressures drive advances in interconnect efficiency, power‑aware partitioning, and intelligent storage hierarchies across AI–multi‑die systems. Collectively, these trends point toward a future where heterogeneous integration and intelligent compute evolve in tandem, delivering new levels of performance, robustness, and environmental efficiency.
Automotive‑grade AI raises the bar further, requiring multi‑die reliability that meets rigorous functional‑safety demands. Sustainability pressures drive advances in interconnect efficiency, power‑aware partitioning, and intelligent storage hierarchies across AI–multi‑die systems. Collectively, these trends point toward a future where heterogeneous integration and intelligent compute evolve in tandem, delivering new levels of performance, robustness, and environmental efficiency.
Organizer
Moderator
Event Type
Engineering Special Session
TimeWednesday, July 2910:30am - 12:00pm PDT
LocationSeaside RM 7
AI
Chiplet
Design
EDA
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