TY - GEN
T1 - Work-in-progress
T2 - 2019 International Conference on Hardware/Software Codesign and System Synthesis, CODES/ISSS 2019
AU - Park, Kyungchul
AU - Yi, Youngmin
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/10/13
Y1 - 2019/10/13
N2 - Recently, there have been attempts to execute the neural network conditionally with auxiliary classifiers allowing early termination depending on the difficulty of the input, which can reduce the execution time or energy consumption without any or with negligible accuracy decrease. However, these studies do not consider how many or where the auxiliary classifiers, or branches, should be added in a systematic fashion. In this paper, we propose Branch-pruned Conditional Neural Network (BPNet) and its methodology in which the time-accuracy tradeoff for the conditional neural network can be found systematically. We applied BPNet to SqueezeNet, ResNet-20, and VGG-16 with CIFAR-10 and 100. BPNet achieves on average 2.0× of speedups without any accuracy drop on average compared to the base network.
AB - Recently, there have been attempts to execute the neural network conditionally with auxiliary classifiers allowing early termination depending on the difficulty of the input, which can reduce the execution time or energy consumption without any or with negligible accuracy decrease. However, these studies do not consider how many or where the auxiliary classifiers, or branches, should be added in a systematic fashion. In this paper, we propose Branch-pruned Conditional Neural Network (BPNet) and its methodology in which the time-accuracy tradeoff for the conditional neural network can be found systematically. We applied BPNet to SqueezeNet, ResNet-20, and VGG-16 with CIFAR-10 and 100. BPNet achieves on average 2.0× of speedups without any accuracy drop on average compared to the base network.
UR - http://www.scopus.com/inward/record.url?scp=85077340365&partnerID=8YFLogxK
U2 - 10.1145/3349567.3351721
DO - 10.1145/3349567.3351721
M3 - Conference contribution
AN - SCOPUS:85077340365
T3 - Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion, CODES/ISSS 2019
BT - Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion, CODES/ISSS 2019
PB - Association for Computing Machinery, Inc
Y2 - 13 October 2019 through 18 October 2019
ER -