Skip to main navigation Skip to search Skip to main content

SHWCIM: A Scalable Heterogeneous Workload Computing-in-Memory Architecture

  • Yanfeng Yang
  • , Yi Zou*
  • , Zhibiao Xue
  • , Liuyang Zhang
  • *Corresponding author for this work
  • South China University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study introduces HWCIM, a SRAM-based Computing-In-Memory core, and SHWCIM, a CIM-capable Coarse-Grained Reconfigurable Architecture, to enhance re-source utilization, multi-functionality, and on-chip memory size in SRAM-based CIM designs. Evaluated using the SMIC 55nm process, HWCIM achieves 1.6x lower power, 2.8x higher energy efficiency, and up to 4.1x smaller area compared to previous CIM and CGRA works. Additionally, SHWCIM delivers an average 105.9x speedup over existing CGRAs and consumes 2-5x less energy than the Nvidia A40 GPU on realistic workloads.

Original languageEnglish
Title of host publication2025 Design, Automation and Test in Europe Conference, DATE 2025 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9783982674100
DOIs
StatePublished - 2025
Event2025 Design, Automation and Test in Europe Conference, DATE 2025 - Lyon, France
Duration: 31 Mar 20252 Apr 2025

Publication series

NameProceedings -Design, Automation and Test in Europe, DATE
ISSN (Print)1530-1591

Conference

Conference2025 Design, Automation and Test in Europe Conference, DATE 2025
Country/TerritoryFrance
CityLyon
Period31/03/252/04/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Fingerprint

Dive into the research topics of 'SHWCIM: A Scalable Heterogeneous Workload Computing-in-Memory Architecture'. Together they form a unique fingerprint.

Cite this