28 citations · 128 across the 19 of their papers we have counts for
4 papers · 1 filter
A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation
Geng Yuan, Xiaolong Ma, Sheng Lin +2
The computing wall and data movement challenges of deep neural networks (DNNs) have exposed the limitations of conventional CMOS-based DNN accelerators. Furthermore, the deep struc…
Non-Structured DNN Weight Pruning -- Is It Beneficial in Any Platform?
Xiaolong Ma, Sheng Lin, Shaokai Ye +10
Large deep neural network (DNN) models pose the key challenge to energy efficiency due to the significantly higher energy consumption of off-chip DRAM accesses than arithmetic or S…
ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning
Xiaolong Ma, Geng Yuan, Sheng Lin +3
The state-of-art DNN structures involve high computation and great demand for memory storage which pose intensive challenge on DNN framework resources. To mitigate the challenges,…
Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM
Shaokai Ye, Xiaoyu Feng, Tianyun Zhang +11
Weight pruning and weight quantization are two important categories of DNN model compression. Prior work on these techniques are mainly based on heuristics. A recent work developed…