Abstract

A number of recent efforts have attempted to design accelerators for popular machine learning algorithms, such as those involving convolutional and deep neural networks (CNNs and DNNs). These algorithms typically involve a large number of multiply-accumulate (dot-product) operations. A recent project, DaDianNao, adopts a near data processing approach, where a specialized neural functional unit performs all the digital arithmetic operations and receives input weights from adjacent eDRAM banks. This work explores an in-situ processing approach, where memristor crossbar arrays not only store input weights, but are also used to perform dot-product operations in an analog manner. While the use of crossbar memory as…

Citation impact

1,520
total citations
FWCI
81.46
Percentile
100%
References
97
Citations per year

Authors

8

Topics & keywords

Keywords
  • Computer science
  • Throughput
  • Crossbar switch
  • Memristor
  • Pipeline (software)
  • Computer architecture
  • Convolutional neural network
  • Artificial neural network
UN Sustainable Development Goals
  • Affordable and clean energy
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