61 citations · 75 across the 6 of their papers we have counts for
3 papers · 1 filter
Precision Highway for Ultra Low-Precision Quantization
Eunhyeok Park, Dongyoung Kim, Sungjoo Yoo +1
Neural network quantization has an inherent problem called accumulated quantization error, which is the key obstacle towards ultra-low precision, e.g., 2- or 3-bit precision. To re…
Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications
Jongsoo Park, Maxim Naumov, Protonu Basu +25
The application of deep learning techniques resulted in remarkable improvement of machine learning models. In this paper provides detailed characterizations of deep learning models…
Value-aware Quantization for Training and Inference of Neural Networks
Eunhyeok Park, Sungjoo Yoo, Peter Vajda
We propose a novel value-aware quantization which applies aggressively reduced precision to the majority of data while separately handling a small amount of large data in high prec…