EIE: Efficient Inference Engine on Compressed Deep Neural Network

4 February 2016

Song Han

Papers citing "EIE: Efficient Inference Engine on Compressed Deep Neural Network"

50 / 325 papers shown

Title
Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning (Technical Report) Zeke Wang Kaan Kara Hantian Zhang Gustavo Alonso O. Mutlu Ce Zhang 31 34 0 08 Mar 2019
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning P. Whatmough Chuteng Zhou Patrick Hansen S. Venkataramanaiah Jae-sun Seo Matthew Mattina 20 57 0 27 Feb 2019
Efficient Memory Management for GPU-based Deep Learning Systems Junzhe Zhang Sai-Ho Yeung Yao Shu Bingsheng He Wei Wang 26 41 0 19 Feb 2019
Speeding up convolutional networks pruning with coarse ranking Zehao Wang Chengcheng Li Dali Wang Xiangyang Wang Hairong Qi 15 0 0 18 Feb 2019
SiamVGG: Visual Tracking using Deeper Siamese Networks Yuhong Li Xiaofan Zhang Deming Chen ViT 52 47 0 07 Feb 2019
Trading-off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach Nitthilan Kanappan Jayakodi Anwesha Chatterjee Wonje Choi J. Doppa P. Pande 19 27 0 29 Jan 2019
FPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture Yu Ji Youyang Zhang Xinfeng Xie Shuangchen Li Peiqi Wang Xing Hu Youhui Zhang Yuan Xie 25 55 0 28 Jan 2019
Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning Shaohui Lin Rongrong Ji Yuchao Li Cheng Deng Xuelong Li 41 70 0 23 Jan 2019
HyPar: Towards Hybrid Parallelism for Deep Learning Accelerator Array Linghao Song Jiachen Mao Youwei Zhuo Xuehai Qian Hai Helen Li Yiran Chen 30 97 0 07 Jan 2019
Efficient Winograd Convolution via Integer Arithmetic Lingchuan Meng J. Brothers 24 29 0 07 Jan 2019
FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review Ahmad Shawahna S. M. Sait A. El-Maleh 28 374 0 01 Jan 2019
ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers Ao Ren Tianyun Zhang Shaokai Ye Jiayu Li Wenyao Xu Xuehai Qian Xinyu Lin Yanzhi Wang MQ 40 161 0 31 Dec 2018
ORIGAMI: A Heterogeneous Split Architecture for In-Memory Acceleration of Learning Hajar Falahati Pejman Lotfi-Kamran Mohammad Sadrosadati H. Sarbazi-Azad 17 8 0 30 Dec 2018
SQuantizer: Simultaneous Learning for Both Sparse and Low-precision Neural Networks M. Park Xiaofang Xu C. Brick MQ 27 8 0 20 Dec 2018
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs Zhe Li Caiwen Ding Siyue Wang Wujie Wen Youwei Zhuo ... Qinru Qiu Wenyao Xu Xinyu Lin Xuehai Qian Yanzhi Wang MQ 14 64 0 12 Dec 2018
Pre-Defined Sparse Neural Networks with Hardware Acceleration Sourya Dey Kuan-Wen Huang Peter A. Beerel K. Chugg 46 24 0 04 Dec 2018
Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization Siyuan Qiao Zhe Lin Jianming Zhang Alan Yuille 19 23 0 02 Dec 2018
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator Jonathan Lew Deval Shah Suchita Pati Shaylin Cattell Mengchi Zhang ... Christopher Ng Negar Goli Matthew D. Sinclair Timothy G. Rogers Tor M. Aamodt 29 65 0 18 Nov 2018
QUENN: QUantization Engine for low-power Neural Networks Miguel de Prado Maurizio Denna Luca Benini Nuria Pazos MQ 40 14 0 14 Nov 2018
Fast On-the-fly Retraining-free Sparsification of Convolutional Neural Networks Amir H. Ashouri T. Abdelrahman Alwyn Dos Remedios MQ 16 12 0 10 Nov 2018
Learning to Skip Ineffectual Recurrent Computations in LSTMs A. Ardakani Zhengyun Ji W. Gross 13 16 0 09 Nov 2018
A First Look at Deep Learning Apps on Smartphones Mengwei Xu Jiawei Liu Yuanqiang Liu F. Lin Yunxin Liu Xuanzhe Liu HAI 33 179 0 08 Nov 2018
To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference Qing Qin Jie Ren Jia-Le Yu Ling Gao Hai Wang Jie Zheng Yansong Feng Jianbin Fang Zheng Wang 16 21 0 21 Oct 2018
SCALE-Sim: Systolic CNN Accelerator Simulator A. Samajdar Yuhao Zhu P. Whatmough Matthew Mattina Tushar Krishna 30 137 0 16 Oct 2018
Morph: Flexible Acceleration for 3D CNN-based Video Understanding Kartik Hegde R. Agrawal Yulun Yao Christopher W. Fletcher 33 71 0 16 Oct 2018
Training Deep Neural Network in Limited Precision Hyunsun Park J. Lee Youngmin Oh Sangwon Ha Seungwon Lee 19 9 0 12 Oct 2018
Dynamic Channel Pruning: Feature Boosting and Suppression Xitong Gao Yiren Zhao Łukasz Dudziak Robert D. Mullins Chengzhong Xu 42 311 0 12 Oct 2018
Rethinking the Value of Network Pruning Zhuang Liu Mingjie Sun Tinghui Zhou Gao Huang Trevor Darrell 10 1,452 0 11 Oct 2018
ProxQuant: Quantized Neural Networks via Proximal Operators Yu Bai Yu Wang Edo Liberty MQ 24 117 0 01 Oct 2018
Mini-batch Serialization: CNN Training with Inter-layer Data Reuse Sangkug Lym Armand Behroozi W. Wen Ge Li Yongkee Kwon M. Erez 17 25 0 30 Sep 2018
To compress or not to compress: Understanding the Interactions between Adversarial Attacks and Neural Network Compression Yiren Zhao Ilia Shumailov Robert D. Mullins Ross J. Anderson AAML 19 43 0 29 Sep 2018
Shift-based Primitives for Efficient Convolutional Neural Networks Huasong Zhong Xianggen Liu Yihui He Yuchun Ma 35 20 0 22 Sep 2018
High Performance Zero-Memory Overhead Direct Convolutions Jiyuan Zhang F. Franchetti Tze Meng Low 19 68 0 20 Sep 2018
MBS: Macroblock Scaling for CNN Model Reduction Yu-Hsun Lin Chun-Nan Chou Edward Y. Chang MQ 16 4 0 18 Sep 2018
Interstellar: Using Halide's Scheduling Language to Analyze DNN Accelerators Xuan S. Yang Mingyu Gao Qiaoyi Liu Jeff Setter Jing Pu ... Kaidi Cao Heonjae Ha Priyanka Raina Christos Kozyrakis M. Horowitz 32 227 0 10 Sep 2018
Fast and Efficient Information Transmission with Burst Spikes in Deep Spiking Neural Networks Seongsik Park Seijoon Kim Hyeokjun Choe Sungroh Yoon 25 94 0 10 Sep 2018
CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams Lukas Cavigelli Luca Benini 27 26 0 15 Aug 2018
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware A. Samajdar Parth Mannan K. Garg T. Krishna 32 20 0 03 Aug 2018
Design Flow of Accelerating Hybrid Extremely Low Bit-width Neural Network in Embedded FPGA Junsong Wang Qiuwen Lou Xiaofan Zhang Chao Zhu Yonghua Lin Deming Chen MQ 36 93 0 31 Jul 2018
PCNNA: A Photonic Convolutional Neural Network Accelerator A. Mehrabian Yousra Alkabani V. Sorger T. El-Ghazawi 21 64 0 23 Jul 2018
Recent Advances in Deep Learning: An Overview Matiur Rahman Minar Jibon Naher VLM 29 116 0 21 Jul 2018
A Hardware-Software Blueprint for Flexible Deep Learning Specialization T. Moreau Tianqi Chen Luis Vega Jared Roesch Eddie Q. Yan ... Josh Fromm Ziheng Jiang Luis Ceze Carlos Guestrin Arvind Krishnamurthy 32 70 0 11 Jul 2018
Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices Yu-hsin Chen Tien-Ju Yang J. Emer Vivienne Sze MQ 18 70 0 10 Jul 2018
XNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference Francesco Conti Pasquale Davide Schiavone Luca Benini 37 108 0 09 Jul 2018
Restructuring Batch Normalization to Accelerate CNN Training Wonkyung Jung Daejin Jung and Byeongho Kim Sunjung Lee Wonjong Rhee Jung Ho Ahn 24 62 0 04 Jul 2018
SYQ: Learning Symmetric Quantization For Efficient Deep Neural Networks Julian Faraone Nicholas J. Fraser Michaela Blott Philip H. W. Leong MQ 33 133 0 01 Jul 2018
Quantizing deep convolutional networks for efficient inference: A whitepaper Raghuraman Krishnamoorthi MQ 50 997 0 21 Jun 2018
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework Mohsen Imani Mohammad Samragh Yeseong Kim Saransh Gupta F. Koushanfar Tajana Simunic 24 51 0 15 Jun 2018
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking Haichuan Yang Yuhao Zhu Ji Liu CVBM 19 36 0 12 Jun 2018
EasyConvPooling: Random Pooling with Easy Convolution for Accelerating Training and Testing Jianzhong Sheng Chuanbo Chen Chenchen Fu Chun Jason Xue 24 4 0 05 Jun 2018