April 3, 2024, 4:43 a.m. | Guodong Yin, Mufeng Zhou, Yiming Chen, Wenjun Tang, Zekun Yang, Mingyen Lee, Xirui Du, Jinshan Yue, Jiaxin Liu, Huazhong Yang, Yongpan Liu, Xueqing Li

cs.LG updates on arXiv.org arxiv.org

arXiv:2212.04320v2 Announce Type: replace-cross
Abstract: Performing data-intensive tasks in the von Neumann architecture is challenging to achieve both high performance and power efficiency due to the memory wall bottleneck. Computing-in-memory (CiM) is a promising mitigation approach by enabling parallel in-situ multiply-accumulate (MAC) operations within the memory with support from the peripheral interface and datapath. SRAM-based charge-domain CiM (CD-CiM) has shown its potential of enhanced power efficiency and computing accuracy. However, existing SRAM-based CD-CiM faces scaling challenges to meet the throughput …

abstract analog architecture arxiv computing cs.ar cs.lg data domain efficiency enabling in-memory mac macro memory network performance power tasks type

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