19 citations · 24 across the 2 of their papers we have counts for
5 papers
Mixed-Precision Embedding Using a Cache
Jie Amy Yang, Jianyu Huang, Jongsoo Park +2
In recommendation systems, practitioners observed that increase in the number of embedding tables and their sizes often leads to significant improvement in model performances. Give…
Hybrid Composition with IdleBlock: More Efficient Networks for Image Recognition
Bing Xu, Andrew Tulloch, Yunpeng Chen +2
We propose a new building block, IdleBlock, which naturally prunes connections within the block. To fully utilize the IdleBlock we break the tradition of monotonic design in state-…
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…
On Periodic Functions as Regularizers for Quantization of Neural Networks
Maxim Naumov, Utku Diril, Jongsoo Park +3
Deep learning models have been successfully used in computer vision and many other fields. We propose an unorthodox algorithm for performing quantization of the model parameters. I…
High performance ultra-low-precision convolutions on mobile devices
Andrew Tulloch, Yangqing Jia
Many applications of mobile deep learning, especially real-time computer vision workloads, are constrained by computation power. This is particularly true for workloads running on…