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Compute-in-Memory (CIM) using emerging nonvolatile (eNVM) memory technologies, such as resistive random-access memory (RRAM), has been shown by several implemented macros to be an energy-efficient alternative to traditional von Neumann architectures 1–6. Since moving data on- and off-chip has a high energy cost, area efficiency is important to the practical utility of CIM with RRAM. Many systems demonstrated so far have not reported area efficiency or addressed the challenges CIM with RRAM presents with respect to practical area-constrained integrated circuits.
Spetalnick et al. (Sun,) studied this question.