可靠性(半导体)
光学(聚焦)
计算机科学
可靠性工程
工程类
钥匙(锁)
系统工程
CMOS芯片
组分(热力学)
风险分析(工程)
作者
Hussam Amrouch,Dragomir Milojevic,Giorgio Di Natale,Jérome Toublanc
标识
DOI:10.23919/date69613.2026.11539746
摘要
AI workloads are driving exceptional demand for performance and energy efficiency, forcing semiconductor innovation to advance along two major directions simultaneously. On the device roadmap, the transition from FinFETs to gate-all-around nanosheet FETs and, subsequently, monolithic 3D Complementary FETs (CFETs) is enabling scaling toward the 2 nm era and beyond while targeting aggressive logic density. In parallel, advanced packaging, spanning 2.5D integration on silicon interposers, true 3D stacking, and hybrid 5.5D assemblies, is becoming essential to deliver ultra-high bandwidth, low-energy die-to-die connectivity required by rapidly growing AI model sizes and the resulting memory-wall bottlenecks. This focus session discusses the opportunities and challenges of this co-evolution, with emphasis on system-technology co-optimization and the inevitable need for multiphysics analysis across electrical, thermal, mechanical, and reliability domains. We highlight how reliability and security concerns are increasingly shaping architectural and packaging choices, and we discuss the role of deep learning as a practical enabler for faster simulation and design-space exploration under rising complexity.
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