静态随机存取存储器
计算机科学
并行计算
瓶颈
冯·诺依曼建筑
宏
计算机硬件
嵌入式系统
吞吐量
高效能源利用
延迟(音频)
晶体管
CMOS芯片
电压
电子工程
电气工程
工程类
操作系统
电信
程序设计语言
无线
作者
Zhiting Lin,Zhongzhen Tong,Fang‐Ming Wang,Jin Zhang,Yue Zhao,Peng Sun,Xu Tian,Cheng Zhang,Xingwei Li,Xiulong Wu,Wenjuan Lu,Chunyu Peng,Qiang Zhao,Junning Chen
出处
期刊:IEEE Journal of Solid-state Circuits
[Institute of Electrical and Electronics Engineers]
日期:2022-09-27
卷期号:58 (5): 1472-1486
被引量:20
标识
DOI:10.1109/jssc.2022.3206318
摘要
Computing in-memory (CIM) is a promising new computing method to solve problems caused by von Neumann bottlenecks. It mitigates the need for transmitting large amounts of data between the processing and memory units, significantly decreasing the latency and energy consumption. However, writing back the calculation results for CIM can become a new bottleneck if only parallel computing is implemented. This study proposes a bidirectional static random access memory (SRAM) array structure comprising self-cycling eight-transistor (8T) cells, which can achieve full-array Boolean logic operations and read/write in two directions. The CIM results can be restored in in situ bit cells in a single cycle without additional memory. In addition, any data row can be copied into another row by controlling the intermediate transistor in the 8T cell. A 16-kb SRAM was implemented in the 28-nm CMOS technology to verify the effectiveness of the proposed design. The throughput of the proposed CIM macro is 1851.4 GOPS. Compared with the existing CIM macros, the throughput increased 3–56.6 times and the energy efficiency was as high as 270.5 TOPS/W at a supply voltage of 0.66 V. When the proposed circuits were applied to advanced encryption standard (AES) algorithms, the energy efficiency is increased by about 47.5%–63% compared to the von Neumann architecture.
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