A2Q: Accumulator-Aware Quantization with Guaranteed Overflow Avoidance

25 August 2023

Papers citing "A2Q: Accumulator-Aware Quantization with Guaranteed Overflow Avoidance"

6 / 6 papers shown

Title
Shedding the Bits: Pushing the Boundaries of Quantization with Minifloats on FPGAs Shivam Aggarwal Hans Jakob Damsgaard Alessandro Pappalardo Giuseppe Franco Thomas B. Preußer Michaela Blott Tulika Mitra MQ 21 5 0 21 Nov 2023
Deep Neural Networks for Encrypted Inference with TFHE Andrei Stoian Jordan Fréry Roman Bredehoft Luis Montero Celia Kherfallah Benoît Chevallier-Mames FedML 38 21 0 13 Feb 2023
An Energy-Efficient Edge Computing Paradigm for Convolution-based Image Upsampling Ian Colbert Ken Kreutz-Delgado Srinjoy Das 41 4 0 15 Jul 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 141 684 0 31 Jan 2021
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 950 20,567 0 17 Apr 2017
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 198 5,176 0 16 Sep 2016