DAMIL-DCIM+: Automated Dataflow-Aware Layout Synthesis for Digital CIM With Self-Assembled Bitcell Units and MILP-Based Optimization

Digital computing-in-memory (DCIM) systems integrate complex digital logic with parasitic-sensitive bitcell arrays, presenting unique physical design challenges. Conventional design strategies often fall short in these systems due to irregular dataflow patterns and excessive interconnect lengths, which degrade performance and increase parasitic effects. As a result, current DCIM implementations frequently rely on manual layout, which is both time-consuming and a major bottleneck in the design cycle. While existing DCIM layout synthesis frameworks attempt to automate this process using template-based placement methods inspired by manual design, their rigid constraints can lead to inefficient area utilization and increased core sizes. To address these limitations, we propose DAMIL-DCIM+, a novel placement framework that combines the structural clarity of template-based methods with the flexibility of optimization-based techniques. Specifically, DAMIL-DCIM+ employs a global dataflow-aware floorplan to guide placement and leverages MILP-based detailed placement to optimize wirelength and preserve dataflow regularity. Inspired by self-assembling design principles, this approach enables scalable and structured integration of parasitic-sensitive components. The hybrid methodology of DAMIL-DCIM+ reduces total wirelength, lowers parasitic effects, and enhances performance while maintaining design regularity. Experimental results on a 28nm DCIM circuit demonstrate that DAMIL-DCIM+ improves operating frequency by 25.2% and reduces power consumption by 19.6% compared to Cadence Innovus, without increasing core area.

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Publication Details

Journal
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Published
2025-09-09
DOI
https://doi.org/10.1109/tcad.2025.3608064
Primary Topic
Advanced Data Storage Technologies
Type
article
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article

DAMIL-DCIM+: Automated Dataflow-Aware Layout Synthesis for Digital CIM With Self-Assembled Bitcell Units and MILP-Based Optimization

Zecheng Xu, Fan Yang, Xuebing Yan, Xuan Zeng et al.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Advanced Data Storage Technologies
article

DAMIL-DCIM+: Automated Dataflow-Aware Layout Synthesis for Digital CIM With Self-Assembled Bitcell Units and MILP-Based Optimization

Zecheng Xu, Fan Yang, Xuebing Yan, Xuan Zeng, Keren Zhu, Shuo Li, Ke Hu, Chuyu Wang
article en

Abstract

Digital computing-in-memory (DCIM) systems integrate complex digital logic with parasitic-sensitive bitcell arrays, presenting unique physical design challenges. Conventional design strategies often fall short in these systems due to irregular dataflow patterns and excessive interconnect lengths, which degrade performance and increase parasitic effects. As a result, current DCIM implementations frequently rely on manual layout, which is both time-consuming and a major bottleneck in the design cycle. While existing DCIM layout synthesis frameworks attempt to automate this process using template-based placement methods inspired by manual design, their rigid constraints can lead to inefficient area utilization and increased core sizes. To address these limitations, we propose DAMIL-DCIM+, a novel placement framework that combines the structural clarity of template-based methods with the flexibility of optimization-based techniques. Specifically, DAMIL-DCIM+ employs a global dataflow-aware floorplan to guide placement and leverages MILP-based detailed placement to optimize wirelength and preserve dataflow regularity. Inspired by self-assembling design principles, this approach enables scalable and structured integration of parasitic-sensitive components. The hybrid methodology of DAMIL-DCIM+ reduces total wirelength, lowers parasitic effects, and enhances performance while maintaining design regularity. Experimental results on a 28nm DCIM circuit demonstrate that DAMIL-DCIM+ improves operating frequency by 25.2% and reduces power consumption by 19.6% compared to Cadence Innovus, without increasing core area.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsVol. 45(4)
Fudan University (CN), Shanghai Fudan Microelectronics (China) (CN)
Openalex Percentile: Top 72%
Advanced Data Storage Technologies
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