Analog In-Memory Computing (AIMC) is a promising technology for deep learning inference due to its speed and energy efficiency. It performs computational tasks within the memory, improving energy efficiency and latency. However, AIMC faces challenges related to circuit mismatches and memory device nonidealities. To overcome these, the Near Memory digital Processing Unit (NMPU) is proposed. The NMPU, implemented in a 14 nm CMOS technology, provides a speedup, smaller area, and competitive power consumption. Despite its potential, further research is needed to fully realize its capabilities and address any challenges.
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