A 28nm Nonvolatile AI Edge Processor using 4Mb Analog-Based Near-Memory-Compute ReRAM with 27.2 TOPS/W for Tiny AI Edge Devices

Tiny AI edge processors prefer using nvCIM to achieve low standby power, high energy efficiency (EF), and short wakeupto-response latency (T WR ). Most nvCIMs use in-memory computing for MAC operations; however, this imposes a tradeoff between EF and accuracy, due to MAC accumulationnumber (N ACU ) versus signal margin and readout quantization. To achieve high EF and high accuracy, we developed a systemlevel nvCIM-friendly control scheme and a nvCIM macro with two analog near-memory computing schemes. The proposed 28nm nonvolatile AI edge processor with 4Mb ReRAMnvCIM achieved high EF (27.2 TOPS/W), short T WR (3.19 ms), and low accuracy loss (<0.5%) The EF of the ReRAM-nvCIM macro was 38.6 TOPS/W.