Neural Networks Weights Quantization: Target None-retraining Ternary (TNT)

18 Dec 2019Tianyu ZhangLei ZhuQian ZhaoKilho Shin

Quantization of weights of deep neural networks (DNN) has proven to be an effective solution for the purpose of implementing DNNs on edge devices such as mobiles, ASICs and FPGAs, because they have no sufficient resources to support computation involving millions of high precision weights and multiply-accumulate operations. This paper proposes a novel method to compress vectors of high precision weights of DNNs to ternary vectors, namely a cosine similarity based target non-retraining ternary (TNT) compression method... (read more)

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