A Dynamic Power-Only Compute-in-Memory Macro With Power-of-Two Nonlinear SAR ADC for Nonvolatile Ferroelectric Capacitive Crossbar Array

Injune Yeo, Wangxin He, Yuan Chun Luo, Shimeng Yu, Jae Sun Seo

Research output: Contribution to journalArticlepeer-review

Abstract

Analog computing-in-memory (CIM) using emerging resistive nonvolatile memory (NVM) technologies faces challenges, such as static power consumption, current flow-induced IR drop, and the need for multiple power-hungry ADCs. In this letter, we present ferroelectric capacitive array (FCA)-based energy/area-efficient CIM macro used for charge-domain multiply-and-accumulate operations, which addresses the challenges of resistive NVM CIMs. The proposed CIM macro involves encoding ternary input activations and weights into voltages, and enabling parasitic insensitive charge readout. A power-of-two nonlinear SAR ADC is introduced, designed for energy-efficiency and hardware-friendliness. This ADC employs adaptive conversion skipping based on input voltage, resulting in fine precision for concentrated input levels and coarse conversion for sparse input levels. The proposed FCA-based CIM macro in 180-nm CMOS demonstrates 16times 8 analog MAC operation with an energy efficiency of 1.75 TOPS/W and classification accuracy of 90.2% is obtained for the CIFAR-10 dataset.

Original languageEnglish (US)
Pages (from-to)70-73
Number of pages4
JournalIEEE Solid-State Circuits Letters
Volume7
DOIs
StatePublished - 2024
Externally publishedYes

Keywords

  • Charge multiply-and-accumulate operation
  • compute-in-memory
  • ferroelectric capacitor array
  • SAR ADC

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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