DS-CIM: Digital Stochastic Computing-In-Memory Featuring Accurate OR-Accumulation via Sample Region Remapping for Edge AI Models

• URL: http://arxiv.org/abs/2601.06724v1
• Date: Sat, 10 Jan 2026 23:56:33 GMT
• Title: DS-CIM: Digital Stochastic Computing-In-Memory Featuring Accurate OR-Accumulation via Sample Region Remapping for Edge AI Models
• Authors: Kunming Shao, Liang Zhao, Jiangnan Yu, Zhipeng Liao, Xiaomeng Wang, Yi Zou, Tim Kwang-Ting Cheng, Chi-Ying Tsui,
• Abstract summary: This paper introduces a digital CIM (DS-CIM) architecture that achieves both high accuracy and efficiency.<n>We implement multiply-accumulation (MAC) in a compact, unsigned OR-based circuit by modifying the data representation.<n>Our core strategy, a shared Random Number Generator (PRNG) with 2D, enables single-cycle mutually exclusive activation to eliminate OR-gate collisions.
• Score: 8.92683306412944
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Stochastic computing (SC) offers hardware simplicity but suffers from low throughput, while high-throughput Digital Computing-in-Memory (DCIM) is bottlenecked by costly adder logic for matrix-vector multiplication (MVM). To address this trade-off, this paper introduces a digital stochastic CIM (DS-CIM) architecture that achieves both high accuracy and efficiency. We implement signed multiply-accumulation (MAC) in a compact, unsigned OR-based circuit by modifying the data representation. Throughput is enhanced by replicating this low-cost circuit 64 times with only a 1x area increase. Our core strategy, a shared Pseudo Random Number Generator (PRNG) with 2D partitioning, enables single-cycle mutually exclusive activation to eliminate OR-gate collisions. We also resolve the 1s saturation issue via stochastic process analysis and data remapping, significantly improving accuracy and resilience to input sparsity. Our high-accuracy DS-CIM1 variant achieves 94.45% accuracy for INT8 ResNet18 on CIFAR-10 with a root-mean-squared error (RMSE) of just 0.74%. Meanwhile, our high-efficiency DS-CIM2 variant attains an energy efficiency of 3566.1 TOPS/W and an area efficiency of 363.7 TOPS/mm^2, while maintaining a low RMSE of 3.81%. The DS-CIM capability with larger models is further demonstrated through experiments with INT8 ResNet50 on ImageNet and the FP8 LLaMA-7B model.

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