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ISSCC 2026Session 15 · DRAM, SRAM, AND NON-VOLATILE MEMORIESMemory2nm CMOS Nanosheet

A 350mV Single-Rail SRAM Using a Custom-Logic-Bitcell in 2nm-CMOS-Nanosheet Technology for Mobile and Edge-AI Applications

⚡ 本页包含 AI 生成的分析内容,仅供参考

📋 论文概要

本文提出了一种在2nm纳米片CMOS技术中实现的单轨、逻辑位单元2端口SRAM,采用2R×1C配置和双位线设计以实现高面积密度和动态功耗优化。该SRAM可在0.35V至1.2V电压下可靠工作,读访问时间达102ps,支持4GHz处理器,适用于移动和边缘AI应用中的浅深度缓存。

💡 主要创新点

核心指标
21.04Mb/mm², 102ps read-access, 0.35-1.2V, 4GHz
工艺节点
2nm CMOS Nanosheet
重要性
发表年份
ISSCC 2026

🏷 关键词

单轨SRAM逻辑位单元2nm纳米片边缘AI浅深度缓存

📄 原文摘要

Abstract This work presents a single-rail, 21.04Mb/mm2 logic-bitcell 2-port SRAM in a 2nm nanosheet technology for CPU, GPU and NPU caches. The implemented xBIT cell in a 2R×1C configuration uses dual BL for balanced NMOS/PMOS devices to form a rectangular array and maximize area density. Optimized for dynamic power, it operates reliably from 0.35 - 1.2V, achieving an industry-leading 102ps read-access time to support 4GHz processor and making it ideal for shallow-depth caches. SRAM is critical in modern compute systems for optimizing system-level power, performance, and area (PPA). For CPUs, GPUs and NPUs it provides low-latency memory access in the form of caches, register files or scratchpads; thereby, accelerating data access and storing weights to support high-speed processing. In addition, these systems use voltage-frequency scaling to improve efficiency, requiring SRAM to function across a wide

👥 作者与机构

Manish Trivedi1, Sandipan Sinha1, Ramesh Halli1, Girishankar Gurumurthy1, Jaswinder Singh1, Chun-Yuan Cheng2, Linchien Chen2, Jeff Lin2, Hugh Mair3

MediaTek, Bengaluru, India, 2MediaTek, Hsinchu, Taiwan, 3MediaTek, Austin, TX

分类:Memory · 年份:ISSCC 2026