TY - GEN
T1 - Increasing PE Utilization with a SW/HW Co-Design Technique for Sparse Convolutional Neural Networks
AU - Tseng, Wei Fan
AU - Lai, Bo Cheng
AU - Pan, Jyun Wei
N1 - Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/10
Y1 - 2019/10
N2 - Pruning convolution neural networks (CNN) has proved to be an effective technique to decrease the network size without loss of accuracy. By processing the compressed format of the network, the energy consumption can be considerably reduced. However, the existing SIMD-like sparse CNN accelerator suffers from low processing engine (PE) utilization due to the irregular distribution of effectual pairs. In this paper, we address this issue by proposing a software and hardware codesign technique, including a novel data compression scheme and a dedicated module to handle this compressed format. When compared to a state-of-the-art SIMD-like accelerator, the proposed co-design technique can reduce the computation time of conv3, conv4, conv5 of AlexNet by 15%, 33%, 31%.
AB - Pruning convolution neural networks (CNN) has proved to be an effective technique to decrease the network size without loss of accuracy. By processing the compressed format of the network, the energy consumption can be considerably reduced. However, the existing SIMD-like sparse CNN accelerator suffers from low processing engine (PE) utilization due to the irregular distribution of effectual pairs. In this paper, we address this issue by proposing a software and hardware codesign technique, including a novel data compression scheme and a dedicated module to handle this compressed format. When compared to a state-of-the-art SIMD-like accelerator, the proposed co-design technique can reduce the computation time of conv3, conv4, conv5 of AlexNet by 15%, 33%, 31%.
KW - Machine learning
KW - SIMD architecture
KW - Sparse convolution neural networks
UR - http://www.scopus.com/inward/record.url?scp=85094664208&partnerID=8YFLogxK
U2 - 10.1109/ICICE49024.2019.9117552
DO - 10.1109/ICICE49024.2019.9117552
M3 - Conference contribution
AN - SCOPUS:85094664208
T3 - Proceedings of the 2019 8th International Conference on Innovation, Communication and Engineering, ICICE 2019
SP - 74
EP - 77
BT - Proceedings of the 2019 8th International Conference on Innovation, Communication and Engineering, ICICE 2019
A2 - Chang, Shoou-Jinn
A2 - Young, Sheng-Joue
A2 - Lam, Artde Donald Kin-Tak
A2 - Ji, Liang-Wen
A2 - Lu, Hao-Ying
A2 - Prior, Stephen D.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Innovation, Communication and Engineering, ICICE 2019
Y2 - 25 October 2019 through 30 October 2019
ER -
