Shubham, SaiSaiShubhamPandit, ShubhamShubhamPanditPrasad, KailashKailashPrasadMekie, JoyceeJoyceeMekie2025-08-312025-08-312023-01-01[9798350323481]10.1109/DAC56929.2023.102478932-s2.0-85173071009http://repository.iitgn.ac.in/handle/IITG2025/26941This work introduces PVC-RAM, a process variation aware in-memory computing (IMC) static random-access memory (SRAM) macro designed for efficient convolutional neural network (CNN) inference. PVC-RAM is a charge-domain based compact IMC and is the first fully analog IMC for 4b-weights/4b-inputs MAC operation for deep neural networks in 6T-SRAM to the best of our knowledge. Further, PVC-RAM fully computes 4-bit MAC in the analog domain and requires fewer invocations of the ADCs. Implemented in 28nm technology, PVC-RAM achieves a bitwise throughput of 6964.48 TOPS, which is 1.5× higher than the SOTA, and a bitwise energy efficiency of 75.12 TOPS/W, which is 1.3× higher than the SOTA.falseConference Paper20230cpConference Proceeding0