Full-Array Boolean Logic CIM Macro With Self-Recycling 10T-SRAM Cell for AES Systems
Computing in memory (CIM), which alleviates the need to transfer a large amount of data between processor and memory, significantly reducing latency and energy consumption, is a promising new computing architecture for addressing the von Neumann bottleneck problem. This article proposes a CIM array structure composed of self-recycling 10T static random access memory (SRAM) cells, which can realize orthogonal data writing, and multiple Boolean logical operations for the entire array. The self-recycling and full-array activation characteristics are extremely suitable for accelerating diverse data processing algorithms such as the Advanced Encryption Standard (AES). A 4-kb SRAM is implemented in 55-nm CMOS technology to verify the effectiveness of the design. Compared with other state-of-the-art architectures, the throughput and the operating frequency of the proposed CIM macro are increased to 843 GOPS/kb (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.64\times $</tex-math> </inline-formula>) and 823.7 MHz (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.6\times $</tex-math> </inline-formula>), respectively. The energy efficiency reaches 246.9 TOPS/W. When applied to the AES, the energy consumption is 35.77% less than the digital CIM architecture that is not self-recycling.
Authors
- Ying Pan
- Xiulong Wu (ORCID: https://orcid.org/0000-0002-5012-2570)
- John Long
- Zhiting Lin (ORCID: https://orcid.org/0000-0002-3314-1606)
- Chunyu Peng (ORCID: https://orcid.org/0000-0003-2408-5048)
- Yongliang Zhou (ORCID: https://orcid.org/0000-0002-7327-6759)
- Yang Lou
- Qian Jin (ORCID: https://orcid.org/0000-0002-9500-3735)
- Xin Li (ORCID: https://orcid.org/0000-0002-0125-5254)
- Lintao Chen
- Bang-Li Wu
Institutions
- Anhui University (CN)
Publication Details
- Journal
- IEEE Transactions on Very Large Scale Integration (VLSI) Systems
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1109/tvlsi.2025.3572140
- Citations
- 2
- Primary Topic
- VLSI and Analog Circuit Testing
- Type
- article
- Field-Weighted Citation Impact
- 4.54
Funders
- National Natural Science Foundation of China
- Anhui Provincial Key Research and Development Plan
- Science and Technology Program of Gansu Province