Name
Title | ||
|---|---|---|
Hardware-Friendly Progressive Pruning Framework for CNN Model Compression using Universal Pattern Sets |
Abstract | ||
|---|---|---|
Pattern-based weight pruning on CNNs has been proven an effective model reduction technique. In this paper, we first present how to select hardware-friendly pruning pattern sets that are universal to various models. We then propose a progressive pruning framework, which produces more globally optimized outcomes. Moreover, to the best of our knowledge, this is the first paper dealing with the pruni... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/VLSI-DAT54769.2022.9768087 | 2022 International Symposium on VLSI Design, Automation and Test (VLSI-DAT) |
Keywords | DocType | ISBN |
Design automation,Computational modeling,Very large scale integration,Reduced order systems,Convolutional neural networks | Conference | 978-1-6654-0921-6 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei-Cheng Chou | 1 | 0 | 0.34 |
| Cheng-Wei Huang | 2 | 0 | 0.34 |
| Juinn-Dar Huang | 3 | 270 | 27.42 |