Key points are not available for this paper at this time.
Modern Convolutional Neural Networks (CNNs) are computation and memory intensive. Thus it is crucial to develop hardware accelerators to achieve high performance as well as power/energy-efficiency on resource limited embedded systems. DRAM-based CNN accelerators exhibit great potentials but face inference accuracy and area overhead challenges.
Deng et al. (Tue,) studied this question.