Name
Title | ||
|---|---|---|
SeFAct2: Selective Feature Activation for Energy-Efficient CNNs using Optimized Thresholds |
Abstract | ||
|---|---|---|
This work presents a framework for dynamic energy reduction in hardware accelerators for convolutional neural networks (CNNs). The key idea is based on the early prediction of the features that may be important, with the deactivation of computations related to unimportant features and static bitwidth reduction. The former is applied in late layers of the CNN, while the latter is more effective in ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCAD.2020.3016281 | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Keywords | DocType | Volume |
Feature extraction,Neurons,Training,Testing,Hardware,Biological neural networks,Computer architecture | Journal | 40 |
Issue | ISSN | Citations |
7 | 0278-0070 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farhana Sharmin Snigdha | 1 | 17 | 3.49 |
| Susmita Dey Manasi | 2 | 3 | 2.09 |
| Jiang Hu | 3 | 668 | 65.67 |
| Sachin Sapatnekar | 4 | 4074 | 361.60 |