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A Local Computing Cell and 6T SRAM-Based Computing-in-Memory Macro With 8-b MAC Operation for Edge AI Chips

Xin Si, Yung-Ning Tu, Wei-Hsing Huang, Jian-Wei Su, Pei-Jung Lu, Jinghong Wang, Ta-Wei Liu, Ssu-Yen Wu, Ruhui Liu, Yen-Chi Chou, Yen-Lin Chung, William M. Shih, Chung‐Chuan Lo, Ren-Shuo Liu, Chih-Cheng Hsieh, Kea‐Tiong Tang, Nan-Chun Lien, Wei-Chiang Shih, Yajuan He, Qiang Li, Meng‐Fan Chang

2021IEEE Journal of Solid-State Circuits139 citationsDOI

Abstract

This article presents a computing-in-memory (CIM) structure aimed at improving the energy efficiency of edge devices running multi-bit multiply-and-accumulate (MAC) operations. The proposed scheme includes a 6T SRAM-based CIM (SRAM-CIM) macro capable of: 1) weight-bitwise MAC (WbwMAC) operations to expand the sensing margin and improve the readout accuracy for high-precision MAC operations; 2) a compact 6T local computing cell to perform multiplication with suppressed sensitivity to process variation; 3) an algorithm-adaptive low MAC-aware readout scheme to improve energy efficiency; 4) a bitline header selection scheme to enlarge signal margin; and 5) a small-offset margin-enhanced sense amplifier for robust read operations against process variation. A fabricated 28-nm 64-kb SRAM-CIM macro achieved access times of 4.1-8.4 ns with energy efficiency of 11.5-68.4 TOPS/W, while performing MAC operations with 4- or 8-b input and weight precision.

Topics & Concepts

Static random-access memoryHeaderComputer scienceBitwise operationMacroComputer hardwareSense amplifierEfficient energy useProcess variationOffset (computer science)Energy (signal processing)Embedded systemProcess (computing)EngineeringComputer networkOperating systemElectrical engineeringSemiconductor memoryMathematicsStatisticsProgramming languageAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesSemiconductor materials and devices
A Local Computing Cell and 6T SRAM-Based Computing-in-Memory Macro With 8-b MAC Operation for Edge AI Chips | Litcius