Table 6 Theoretical amount of computation in FLOPs and the corresponding acceleration in practice
From: An efficient pruning scheme of deep neural networks for Internet of Things applications
Archi. | Original FLOPs | Original time (s) | Pruned FLOPs | Pruned time (s) | Acceleration (%) |
|---|---|---|---|---|---|
VGG | 3.13×108 | 0.428 | 1.59×108 | 0.259 | 39.5 |
ResNet-56 | 1.25×108 | 0.256 | 6.43×107 | 0.215 | 16.1 |
MobileNet | 2.97×107 | 0.421 | 1.15×107 | 0.200 | 52.5 |
ResNet-50 | 3.38×109 | 5.453 | 1.71×109 | 4.098 | 25.0 |