2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 2 cited
CHEX: CHannel EXploration for CNN Model Compression
Zejiang Hou, Minghai Qin, Fei Sun +7
Channel pruning has been broadly recognized as an effective technique to reduce the computation and memory cost of deep convolutional neural networks. However, conventional pruning…
cs.DC2022★ 1 cited
Shfl-BW: Accelerating Deep Neural Network Inference with Tensor-Core Aware Weight Pruning
Guyue Huang, Haoran Li, Minghai Qin +3
Weight pruning in deep neural networks (DNNs) can reduce storage and computation cost, but struggles to bring practical speedup to the model inference time. Tensor-cores can signif…
cs.LG2021★ 1 cited
Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation
Nan Wu, Huake He, Yuan Xie +2
Circuit design is complicated and requires extensive domain-specific expertise. One major obstacle stuck on the way to hardware agile development is the considerably time-consuming…