ALBSNN: ultra-low latency adaptive local binary spiking neural network with accuracy loss estimator
Y Pei, C Xu, Z Wu, Y Liu, Y Yang - Frontiers in Neuroscience, 2023 - frontiersin.org
Spiking neural network (SNN) is a brain-inspired model with more spatio-temporal
information processing capacity and computational energy efficiency. However, with the …
information processing capacity and computational energy efficiency. However, with the …
Not all bits have equal value: Heterogeneous precisions via trainable noise
We study the problem of training deep networks while quantizing parameters and activations
into low-precision numeric representations, a setting central to reducing energy …
into low-precision numeric representations, a setting central to reducing energy …
SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks
C Zhou, V Richard, P Savarese, Z Hassman… - arXiv preprint arXiv …, 2023 - arxiv.org
Recent advancements in quantization and mixed-precision techniques offer significant
promise for improving the run-time and energy efficiency of neural networks. In this work, we …
promise for improving the run-time and energy efficiency of neural networks. In this work, we …