English

Cryogenic quasi-static embedded DRAM for energy-efficient compute-in-memory applications

Emerging Technologies 2023-11-21 v1

Abstract

Compute-in-memory (CIM) presents an attractive approach for energy-efficient computing in data-intensive applications. However, the development of suitable memory designs to achieve high-performance CIM remains a challenging task. Here, we propose a cryogenic quasi-static embedded DRAM to address the logic-memory mismatch of CIM. Guided by the re-calibrated cryogenic device model, the designed four-transistor bit-cell achieves full-swing data storage, low power consumption, and extended retention time at cryogenic temperatures. Combined with the adoption of cryogenic write bitline biasing technique and readout circuitry optimization, our 4Kb cryogenic eDRAM chip demonstrates a 1.37×\times106^6 times improvement in retention time, while achieving a 75 times improvement in retention variability, compared to room-temperature operation. Moreover, it also achieves outstanding power performance with a retention power of 112 fW and a dynamic power of 108 μ\muW at 4.2 K, which can be further decreased by 7.1% and 13.6% using the dynamic voltage scaling technique. This work reveals the great potential of cryogenic CMOS for high-density data storage and lays a solid foundation for energy-efficient CIM implementations.

Keywords

Cite

@article{arxiv.2311.11572,
  title  = {Cryogenic quasi-static embedded DRAM for energy-efficient compute-in-memory applications},
  author = {Yuhao Shu and Hongtu Zhang and Hao Sun and Mengru Zhang and Wenfeng Zhao and Qi Deng and Zhidong Tang and Yumeng Yuan and Yongqi Hu and Yu Gu and Xufeng Kou and Yajun Ha},
  journal= {arXiv preprint arXiv:2311.11572},
  year   = {2023}
}
R2 v1 2026-06-28T13:25:45.566Z