AdaptivFloat: A Floating-point based Data Type for Resilient Deep
Learning Inference

AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference

29 September 2019

Vijay Janapa Reddi

Alexander M. Rush

David Brooks

Papers citing "AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference"

6 / 6 papers shown

Title
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training Charbel Sakr Steve Dai Rangharajan Venkatesan B. Zimmer W. Dally Brucek Khailany MQ 27 41 0 13 Jun 2022
Synapse Compression for Event-Based Convolutional-Neural-Network Accelerators Lennart Bamberg Arash Pourtaherian Luc Waeijen A. Chahar Orlando Moreira 14 4 0 13 Dec 2021
Analyzing and Improving Fault Tolerance of Learning-Based Navigation Systems Zishen Wan Aqeel Anwar Yu-Shun Hsiao Tianyu Jia Vijay Janapa Reddi A. Raychowdhury AAML 48 30 0 09 Nov 2021
Elastic Significant Bit Quantization and Acceleration for Deep Neural Networks Cheng Gong Ye Lu Kunpeng Xie Zongming Jin Tao Li Yanzhi Wang MQ 27 7 0 08 Sep 2021
OpenNMT: Open-Source Toolkit for Neural Machine Translation Guillaume Klein Yoon Kim Yuntian Deng Jean Senellart Alexander M. Rush 273 1,896 0 10 Jan 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhehuai Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 718 6,750 0 26 Sep 2016