SLICE-CiM：面向基于SRAM的数字存内计算的选择性逐层推理控制引擎，带基于置信度的提前退出

arXiv:2610.37601v1 Announce Type: cross Abstract: Digital SRAM compute-in-memory (CIM) macros enable energy-efficient CNN inference by eliminating off-chip weight transfers; however, peripheral control logic introduces three inefficiencies: bit- slice over-activation at reduced precision (L1), unnecessary accumula- tion depth (L2), and idle precision-transition stalls (L3). To address these, we present four synthesizable peripheral blocks: a Flush-Merge Enable (FME) controller, a Confidence-Based Early-Exit (EE) module, a Precision Register with Decoder (PR/PD), and a Bit-Serial Cycle Controller (CC), co-designed to minimize switching activity, wordline overhead, and leakage. Implemented in TSMC 65-nm CMOS at 335 MHz, the peripheral framework occupies 1769.760 {\mu}m2 post-synthesis and 1982.131 {\mu}m2 post-PnR. Gate-level VCD analysis reports 6.0706 {\mu}W leakage and 288.2902 {\mu}W (post-synthesis) / 322.8850 {\mu}W (post-PnR) dynamic power, totaling 328.9556 {\mu}W (0.2402% of system power). The EE module dominates dynamic power (58.2%), while WLG dominates area (58.1%). System evaluation on MobileNetV2 (CIFAR-100) shows efficiency scaling from 31.35 TOPS/W (8b/8b, 1.2 V) to 454.91 TOPS/W (2b/8b, 0.8 V), achieving 13.33x improvement without bitcell modification or retraining. The framework targets CNN workloads exploiting sparsity, with Transformer extension as future work.

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