26 citations · 64 across the 21 of their papers we have counts for
4 papers · 1 filter
High Area/Energy Efficiency RRAM CNN Accelerator with Kernel-Reordering Weight Mapping Scheme Based on Pattern Pruning
Songming Yu, Yongpan Liu, Lu Zhang +5
Resistive Random Access Memory (RRAM) is an emerging device for processing-in-memory (PIM) architecture to accelerate convolutional neural network (CNN). However, due to the highly…
Adaptive Pixel-wise Structured Sparse Network for Efficient CNNs
Chen Tang, Wenyu Sun, Zhuqing Yuan +1
To accelerate deep CNN models, this paper proposes a novel spatially adaptive framework that can dynamically generate pixel-wise sparsity according to the input image. The sparse s…
ADMP: An Adversarial Double Masks Based Pruning Framework For Unsupervised Cross-Domain Compression
Xiaoyu Feng, Zhuqing Yuan, Guijin Wang +1
Despite the recent progress of network pruning, directly applying it to the Internet of Things (IoT) applications still faces two challenges, i.e. the distribution divergence betwe…
Low Overhead Online Data Flow Tracking for Intermittently Powered Non-volatile FPGAs
Xinyi Zhang, Clay Patterson, Yongpan Liu +3
Energy harvesting is an attractive way to power future IoT devices since it can eliminate the need for battery or power cables. However, harvested energy is intrinsically unstable.…