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TFApprox: Towards a Fast Emulation of DNN Approximate Hardware
  Accelerators on GPU

TFApprox: Towards a Fast Emulation of DNN Approximate Hardware Accelerators on GPU

21 February 2020
Filip Vaverka
Vojtěch Mrázek
Z. Vašíček
Lukás Sekanina
ArXiv (abs)PDFHTMLGithub (27★)

Papers citing "TFApprox: Towards a Fast Emulation of DNN Approximate Hardware Accelerators on GPU"

12 / 12 papers shown
Title
Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability
Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability
Aikaterini Maria Panteleaki
K. Balaskas
Georgios Zervakis
H. Amrouch
Iraklis Anagnostopoulos
69
1
0
14 Apr 2025
Leveraging Highly Approximated Multipliers in DNN Inference
Leveraging Highly Approximated Multipliers in DNN Inference
Georgios Zervakis
Fabio Frustaci
Ourania Spantidi
Iraklis Anagnostopoulos
H. Amrouch
Jörg Henkel
117
1
0
21 Dec 2024
TransAxx: Efficient Transformers with Approximate Computing
TransAxx: Efficient Transformers with Approximate Computing
Dimitrios Danopoulos
Georgios Zervakis
Dimitrios Soudris
Jörg Henkel
ViT
117
2
0
12 Feb 2024
ApproxTrain: Fast Simulation of Approximate Multipliers for DNN Training
  and Inference
ApproxTrain: Fast Simulation of Approximate Multipliers for DNN Training and Inference
Jing Gong
Hassaan Saadat
Hasindu Gamaarachchi
Haris Javaid
X. Hu
S. Parameswaran
80
18
0
09 Sep 2022
Combining Gradients and Probabilities for Heterogeneous Approximation of
  Neural Networks
Combining Gradients and Probabilities for Heterogeneous Approximation of Neural Networks
E. Trommer
Bernd Waschneck
Akash Kumar
60
8
0
15 Aug 2022
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
94
2
0
31 Jul 2022
Hardware Approximate Techniques for Deep Neural Network Accelerators: A
  Survey
Hardware Approximate Techniques for Deep Neural Network Accelerators: A Survey
Giorgos Armeniakos
Georgios Zervakis
Dimitrios Soudris
J. Henkel
363
100
0
16 Mar 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
94
33
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
51
6
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
50
20
0
20 Jul 2021
Control Variate Approximation for DNN Accelerators
Control Variate Approximation for DNN Accelerators
Georgios Zervakis
Ourania Spantidi
Iraklis Anagnostopoulos
H. Amrouch
J. Henkel
BDL
60
24
0
18 Feb 2021
Evolutionary Neural Architecture Search Supporting Approximate
  Multipliers
Evolutionary Neural Architecture Search Supporting Approximate Multipliers
Michal Pinos
Vojtěch Mrázek
Lukás Sekanina
82
10
0
28 Jan 2021
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