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DeepFire2: A Convolutional Spiking Neural Network Accelerator on FPGAs
Brain-inspired spiking neural networks (SNNs) replace the multiply-accumulate operations of traditional neural networks by integrate-and-fire neurons, with the goal of achieving greater energy efficiency.
DTNN: Energy-efficient Inference with Dendrite Tree Inspired Neural Networks for Edge Vision Applications
DTNN achieved significant energy saving (19. 4X and 64. 9X improvement on ResNet-18 and VGG-11 with ImageNet, respectively) with negligible loss of accuracy.
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