PIM (Processing-in-memory)-based CNN (Convolutional neural network) accelerators leverage the characteristics of basic memory cells to enable simple logic and arithmetic operations so that the bandwidth constraint can be effectively alleviated. However, it remains a major challenge to support multiplication operations efficiently on PIM accelerators, in particular, DRAM-based PIM accelerators. This has prevented PIM-based accelerators from being immediately adopted for accurate CNN inference.
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Deng et al. (2019) studied this question.
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