Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity

12 September 2023

Papers citing "Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity"

20 / 20 papers shown

Title
Revisiting Structured Dropout Yiren Zhao Oluwatomisin Dada Xitong Gao Robert D. Mullins BDL 45 2 0 05 Oct 2022
Skip-Convolutions for Efficient Video Processing A. Habibian Davide Abati Taco S. Cohen B. Bejnordi 87 50 0 23 Apr 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 268 703 0 31 Jan 2021
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices Byung Hoon Ahn Jinwon Lee J. Lin Hsin-Pai Cheng Jilei Hou H. Esmaeilzadeh 87 55 0 04 Mar 2020
Importance Estimation for Neural Network Pruning Pavlo Molchanov Arun Mallya Stephen Tyree I. Frosio Jan Kautz 3DPC 73 866 0 25 Jun 2019
Searching for MobileNetV3 Andrew G. Howard Mark Sandler Grace Chu Liang-Chieh Chen Bo Chen ... Yukun Zhu Ruoming Pang Vijay Vasudevan Quoc V. Le Hartwig Adam 300 6,685 0 06 May 2019
Learned Step Size Quantization S. K. Esser J. McKinstry Deepika Bablani R. Appuswamy D. Modha MQ 65 792 0 21 Feb 2019
DropBlock: A regularization method for convolutional networks Golnaz Ghiasi Nayeon Lee Quoc V. Le 104 911 0 30 Oct 2018
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design Ningning Ma Xiangyu Zhang Haitao Zheng Jian Sun 145 4,957 0 30 Jul 2018
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference Benoit Jacob S. Kligys Bo Chen Menglong Zhu Matthew Tang Andrew G. Howard Hartwig Adam Dmitry Kalenichenko MQ 136 3,090 0 15 Dec 2017
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 157 1,262 0 05 Oct 2017
WRPN: Wide Reduced-Precision Networks Asit K. Mishra Eriko Nurvitadhi Jeffrey J. Cook Debbie Marr MQ 64 267 0 04 Sep 2017
Learning Efficient Convolutional Networks through Network Slimming Zhuang Liu Jianguo Li Zhiqiang Shen Gao Huang Shoumeng Yan Changshui Zhang 113 2,407 0 22 Aug 2017
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression Jian-Hao Luo Jianxin Wu Weiyao Lin 49 1,758 0 20 Jul 2017
Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks Minsoo Rhu Mike O'Connor Niladrish Chatterjee Jeff Pool S. Keckler 52 176 0 03 May 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 1.1K 20,747 0 17 Apr 2017
Pruning Filters for Efficient ConvNets Hao Li Asim Kadav Igor Durdanovic H. Samet H. Graf 3DPC 175 3,687 0 31 Aug 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size F. Iandola Song Han Matthew W. Moskewicz Khalid Ashraf W. Dally Kurt Keutzer 132 7,448 0 24 Feb 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 223 8,793 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 273 6,628 0 08 Jun 2015