TY - GEN
T1 - Supporting compressed-sparse activations and weights on SIMD-like accelerator for sparse convolutional neural networks
AU - Lin, Chien Yu
AU - Lai, Bo-Cheng
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/2/20
Y1 - 2018/2/20
N2 - Sparsity is widely observed in convolutional neural networks by zeroing a large portion of both activations and weights without impairing the result. By keeping the data in a compressed-sparse format, the energy consumption could be considerably cut down due to less memory traffic. However, the wide SIMD-like MAC engine adopted in many CNN accelerators can not support the compressed input due to the data misalignment. In this work, a novel Dual Indexing Module (DIM) is proposed to efficiently handle the alignment issue where activations and weights are both kept in compressed-sparse format. The DIM is implemented in a representative SIMD-like CNN accelerator, and able to exploit both compressed-sparse activations and weights. The synthesis results with 40nm technology have shown that DIM can enhance up to 46% of energy consumption and 55.4% Energy-Delay-Product (EDP).
AB - Sparsity is widely observed in convolutional neural networks by zeroing a large portion of both activations and weights without impairing the result. By keeping the data in a compressed-sparse format, the energy consumption could be considerably cut down due to less memory traffic. However, the wide SIMD-like MAC engine adopted in many CNN accelerators can not support the compressed input due to the data misalignment. In this work, a novel Dual Indexing Module (DIM) is proposed to efficiently handle the alignment issue where activations and weights are both kept in compressed-sparse format. The DIM is implemented in a representative SIMD-like CNN accelerator, and able to exploit both compressed-sparse activations and weights. The synthesis results with 40nm technology have shown that DIM can enhance up to 46% of energy consumption and 55.4% Energy-Delay-Product (EDP).
UR - http://www.scopus.com/inward/record.url?scp=85045316656&partnerID=8YFLogxK
U2 - 10.1109/ASPDAC.2018.8297290
DO - 10.1109/ASPDAC.2018.8297290
M3 - Conference contribution
AN - SCOPUS:85045316656
T3 - Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC
SP - 105
EP - 110
BT - ASP-DAC 2018 - 23rd Asia and South Pacific Design Automation Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd Asia and South Pacific Design Automation Conference, ASP-DAC 2018
Y2 - 22 January 2018 through 25 January 2018
ER -