High-Efficiency and Low-Deviation Analog-Digital Hybrid Compute-in-Memory Architecture With Dynamic Weight Division

Compute-in-memory (CIM) reduces data movement but suffers from an accuracy-efficiency trade-off: Analog CIM (ACIM) is energy-efficient but loses accuracy and incurs higher cost at large bit-widths, while digital CIM (DCIM) supports high precision but is inefficient for low-precision tasks. To overcome these challenges, we propose an analog-digital hybrid CIM (HCIM) architecture to address this trade-off, including 1) an analog-digital hybrid 10T SRAM cell without additional transistors and a dual-capacitor-based multicycle weighting module to reduce area; 2) a successive-approximation-register (SAR) ADC with a pseudo C-2C capacitor array that can be reconfigured from an 8-bit ADC into two parallel 4-bit ADCs to improve configurability; 3) configurable weight division and computing resource allocation strategies. Simulations in a 28-nm process show that HCIM achieves 15.56 TOPS/W at 12-bit (8+4 ) with 1.33× and 2.35× efficiency improvement over DCIM and ACIM and 16× lower error. It achieves 27.87 TOPS/W at 8-bit and 78.13 TOPS/W at 4-bit, demonstrating superior energy efficiency, computational accuracy, and flexibility.