Quantized Neural Network Inference with Precision Batching

26 February 2020

Maximilian Lam

Papers citing "Quantized Neural Network Inference with Precision Batching"

25 / 25 papers shown

Title
AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference Thierry Tambe En-Yu Yang Zishen Wan Yuntian Deng Vijay Janapa Reddi Alexander M. Rush David Brooks Gu-Yeon Wei MQ 32 21 0 29 Sep 2019
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations Tri Dao Albert Gu Matthew Eichhorn Atri Rudra Christopher Ré 93 106 0 14 Mar 2019
Improving Neural Network Quantization without Retraining using Outlier Channel Splitting Ritchie Zhao Yuwei Hu Jordan Dotzel Christopher De Sa Zhiru Zhang OODD MQ 77 308 0 28 Jan 2019
Rethinking floating point for deep learning Jeff Johnson MQ 92 138 0 01 Nov 2018
PACT: Parameterized Clipping Activation for Quantized Neural Networks Jungwook Choi Zhuo Wang Swagath Venkataramani P. Chuang Vijayalakshmi Srinivasan K. Gopalakrishnan MQ 58 947 0 16 May 2018
Word2Bits - Quantized Word Vectors Maximilian Lam MQ 42 26 0 15 Mar 2018
Alternating Multi-bit Quantization for Recurrent Neural Networks Chen Xu Jianqiang Yao Zhouchen Lin Wenwu Ou Yuanbin Cao Zhirong Wang H. Zha MQ 67 116 0 01 Feb 2018
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks Hardik Sharma Jongse Park Naveen Suda Liangzhen Lai Benson Chau Joo-Young Kim Vikas Chandra H. Esmaeilzadeh MQ 53 490 0 05 Dec 2017
Streamlined Deployment for Quantized Neural Networks Yaman Umuroglu Magnus Jahre MQ 41 36 0 12 Sep 2017
On the State of the Art of Evaluation in Neural Language Models Gábor Melis Chris Dyer Phil Blunsom 59 534 0 18 Jul 2017
Training Quantized Nets: A Deeper Understanding Hao Li Soham De Zheng Xu Christoph Studer H. Samet Tom Goldstein MQ 50 210 0 07 Jun 2017
Efficient Processing of Deep Neural Networks: A Tutorial and Survey Vivienne Sze Yu-hsin Chen Tien-Ju Yang J. Emer AAML 3DV 113 3,013 0 27 Mar 2017
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 382 1,050 0 10 Feb 2017
Trained Ternary Quantization Chenzhuo Zhu Song Han Huizi Mao W. Dally MQ 131 1,035 0 04 Dec 2016
Bit-pragmatic Deep Neural Network Computing Jorge Albericio Patrick Judd A. Delmas Sayeh Sharify Andreas Moshovos MQ 76 239 0 20 Oct 2016
Pointer Sentinel Mixture Models Stephen Merity Caiming Xiong James Bradbury R. Socher RALM 252 2,842 0 26 Sep 2016
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations Itay Hubara Matthieu Courbariaux Daniel Soudry Ran El-Yaniv Yoshua Bengio MQ 132 1,861 0 22 Sep 2016
SQuAD: 100,000+ Questions for Machine Comprehension of Text Pranav Rajpurkar Jian Zhang Konstantin Lopyrev Percy Liang RALM 205 8,113 0 16 Jun 2016
EIE: Efficient Inference Engine on Compressed Deep Neural Network Song Han Xingyu Liu Huizi Mao Jing Pu A. Pedram M. Horowitz W. Dally 118 2,455 0 04 Feb 2016
Learning Natural Language Inference with LSTM Shuohang Wang Jing Jiang 89 445 0 30 Dec 2015
Neural Networks with Few Multiplications Zhouhan Lin Matthieu Courbariaux Roland Memisevic Yoshua Bengio 82 331 0 11 Oct 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 227 8,821 0 01 Oct 2015
A large annotated corpus for learning natural language inference Samuel R. Bowman Gabor Angeli Christopher Potts Christopher D. Manning 261 4,278 0 21 Aug 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 279 6,657 0 08 Jun 2015
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 337 20,518 0 10 Sep 2014