期刊
ELECTRONICS
卷 11, 期 22, 页码 -出版社
MDPI
DOI: 10.3390/electronics11223667
关键词
processing-in-memory; in-memory computing; memristor; Resistive Random Access Memory; ReRAM; neural network; CNN; RNN; accelerator
资金
- Xiamen University Malaysia Research Fund [XMUMRF/2022-C9/IECE/0033]
This paper discusses various methods and design schemes for ReRAM-based PIM neural network accelerators, and addresses the limitations or challenges of ReRAM in a neural network.
Processing-in-memory (PIM) is a promising architecture to design various types of neural network accelerators as it ensures the efficiency of computation together with Resistive Random Access Memory (ReRAM). ReRAM has now become a promising solution to enhance computing efficiency due to its crossbar structure. In this paper, a ReRAM-based PIM neural network accelerator is addressed, and different kinds of methods and designs of various schemes are discussed. Various models and architectures implemented for a neural network accelerator are determined for research trends. Further, the limitations or challenges of ReRAM in a neural network are also addressed in this review.
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