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DAMIL-DCIM plus : Automated Dataflow-Aware Layout Synthesis for Digital CIM With Self-Assembled Bitcell Units and MILP-Based Optimization
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DOI：10.1109/TCAD.2025.3608064.png)
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Abstract
En 中文
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 28-nm 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.
Keywords:
Adders
Layout
Computer architecture
Logic
In-memory computing
Physical design
Optimization
Logic arrays
Standards
Power demand
Digital computing-in-memory (DCIM)
electronic design automation
physical design
Journal
I
IF:
2.9
Papers:
564
Citations:
9.6K
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Cited Papers