A 28-nm RRAM/SRAM Collaborative CIM Accelerator Supporting RRAM-Endurance-Latency Awareness for Edge Fine-Tuning
The resistive random access memory (RRAM)-based computing-in-memory features high density and high energy efficiency on edge. However, fine-tuning RRAM-based SoCs remains challenging due to the inherent limitations of non-volatile memory (NVM) characteristics. This work proposes an NVM-endurance/latency-aware collaborative RRAM/static random access memory (SRAM) compute-in-memory (CIM) accelerator that addresses the difficulties associated with RRAM write operations during fine-tuning tasks for both CNN and transformer models. The major contributions are: 1) RRAM-most significant bit (MSB)–SRAM-least significant bit (LSB) (RMSL)-based collaborative CIM macros, mitigating RRAM cell flipping times and alleviating the endurance concern; 2) an RRAM-sparse-SRAM-dense (RSSD) weight updating engine, minimizing the long reading and writing latency associated with RRAM access; and 3) a row-wise pipeline weight gradient (WG) computing data flow with low-hardware overhead. With a maximum bit update of ten times per fine-tuning (20 epochs, from start to convergence), the system achieves an energy efficiency of 76.25 TOPS/W for the CIM macro and 22.07 TOPS/W for the overall system. Thanks to the bit-level collaborative CIM, the RRAM CIM macro achieves the same hardware utilization during fine-tuning and inference processes to support RRAM’s energy-efficient computing. The proposed CIM accelerator, fabricated using 28-nm CMOS technology, achieves up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$143{\times }$</tex-math> </inline-formula> RRAM endurance improvement, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$117{\times }$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$144{\times }$</tex-math> </inline-formula> reduction in RRAM write power and latency.
Authors
- Liang Chen (ORCID: https://orcid.org/0000-0001-9114-1885)
- Yuliang Zhou (ORCID: https://orcid.org/0000-0001-7942-9296)
- Jie Liao (ORCID: https://orcid.org/0000-0002-6697-8998)
- Haozhe Zhu (ORCID: https://orcid.org/0000-0002-6412-3996)
- Jianguo Yang (ORCID: https://orcid.org/0000-0002-3387-1238)
- Chixiao Chen (ORCID: https://orcid.org/0000-0002-5980-4236)
- Chen Mu (ORCID: https://orcid.org/0009-0008-7085-6177)
- Yechu Zhang
- Qi Liu (ORCID: https://orcid.org/0000-0001-7062-831X)
- H. W. Jiang (ORCID: https://orcid.org/0000-0002-3759-2228)
- Z.-X. Huang
Institutions
- Fudan University (CN)
- Shanghai Zhangjiang Laboratory (CN)
Publication Details
- Journal
- IEEE Journal of Solid-State Circuits
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1109/jssc.2025.3577335
- Citations
- 4
- Primary Topic
- VLSI and Analog Circuit Testing
- Type
- article
- Field-Weighted Citation Impact
- 9.08
Funders
- National Natural Science Foundation of China
- Hellenic Foundation for Research and Innovation