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ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network
  Accelerators without Retraining

ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining

11 June 2019
Vojtěch Mrázek
Z. Vašíček
Lukás Sekanina
Muhammad Abdullah Hanif
Muhammad Shafique
ArXivPDFHTML

Papers citing "ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining"

11 / 11 papers shown
Title
EPSILON: Adaptive Fault Mitigation in Approximate Deep Neural Network using Statistical Signatures
EPSILON: Adaptive Fault Mitigation in Approximate Deep Neural Network using Statistical Signatures
Khurram Khalil
K. A. Hoque
AAML
81
0
0
24 Apr 2025
TransAxx: Efficient Transformers with Approximate Computing
TransAxx: Efficient Transformers with Approximate Computing
Dimitrios Danopoulos
Georgios Zervakis
Dimitrios Soudris
Jörg Henkel
ViT
42
2
0
12 Feb 2024
Approximate Computing Survey, Part II: Application-Specific & Architectural Approximation Techniques and Applications
Approximate Computing Survey, Part II: Application-Specific & Architectural Approximation Techniques and Applications
Vasileios Leon
Muhammad Abdullah Hanif
Giorgos Armeniakos
Xun Jiao
Muhammad Shafique
K. Pekmestzi
Dimitrios Soudris
37
3
0
20 Jul 2023
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against
  Adversarial Machine Learning
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against Adversarial Machine Learning
Mohammad Hossein Samavatian
Saikat Majumdar
Kristin Barber
R. Teodorescu
AAML
14
2
0
31 Jul 2022
CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for
  Energy-Efficient Low-precision Deep Convolutional Neural Networks
CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networks
Muhammad Abdullah Hanif
G. M. Sarda
Alberto Marchisio
Guido Masera
Maurizio Martina
Muhammad Shafique
MQ
22
4
0
31 Jul 2022
AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch
AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch
Dimitrios Danopoulos
Georgios Zervakis
K. Siozios
Dimitrios Soudris
J. Henkel
27
31
0
08 Mar 2022
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep
  Neural Networks
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks
Su Zheng
Zhen Li
Yao Lu
Jingbo Gao
Jide Zhang
Lingli Wang
12
5
0
20 Jan 2022
Positive/Negative Approximate Multipliers for DNN Accelerators
Positive/Negative Approximate Multipliers for DNN Accelerators
Ourania Spantidi
Georgios Zervakis
Iraklis Anagnostopoulos
H. Amrouch
J. Henkel
18
18
0
20 Jul 2021
Reliability-Aware Quantization for Anti-Aging NPUs
Reliability-Aware Quantization for Anti-Aging NPUs
Sami Salamin
Georgios Zervakis
Ourania Spantidi
Iraklis Anagnostopoulos
J. Henkel
H. Amrouch
11
13
0
08 Mar 2021
Control Variate Approximation for DNN Accelerators
Control Variate Approximation for DNN Accelerators
Georgios Zervakis
Ourania Spantidi
Iraklis Anagnostopoulos
H. Amrouch
J. Henkel
BDL
26
22
0
18 Feb 2021
Hardware and Software Optimizations for Accelerating Deep Neural
  Networks: Survey of Current Trends, Challenges, and the Road Ahead
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead
Maurizio Capra
Beatrice Bussolino
Alberto Marchisio
Guido Masera
Maurizio Martina
Muhammad Shafique
BDL
56
140
0
21 Dec 2020
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