A 36.2 dB High SNR and PVT/Leakage-Robust eDRAM Computing-In-Memory Macro With Segmented BL and Reference Cell Array

Abstract

Computing-in-memory (CIM) shows high energy-efficiency through the analog DNN computation inside the memory macros. However, as the DNN size increases, the energy-efficiency of CIM is reduced by external memory access (EMA). One of the promising solutions is eDRAM based CIM to increase memory capacity with a high density cell. Although the eDRAM-CIM has a higher density than the SRAM-CIM, it suffers from both poor robustness and a low signal-to-noise ratio (SNR). In this brief, the energy-efficient eDRAM-CIM macro is proposed while improving computational robustness and SNR with three key features: 1) High SNR voltage-based accumulation with segmented BL architecture (SBLA), resulting in 17.1 dB higher SNR, 2) canceling PVT/leakage-induced error with common-mode error canceling (CMEC) circuit, resulting in 51.4&#x0025; PVT variation reduction and 51.4&#x0025; refresh power reduction, 3) a ReLU-based zero-gating ADC (ZG-ADC), resulting in ADC power reduction up to 58.1&#x0025;. According to these new features, the proposed eDRAM-CIM macro achieves 81.5-to-115.0 TOPS/W energy-efficiency with 209-to-295 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power consumption when 4b <inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 4b MAC operation is performed with 250 MHz core frequency. The proposed macro also achieves 91.52&#x0025; accuracy at the CIFAR-10 object classification dataset (ResNet-20) without accuracy drop even with PVT variation.