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Analyzing and Mitigating the Impact of Permanent Faults on a Systolic
  Array Based Neural Network Accelerator

Analyzing and Mitigating the Impact of Permanent Faults on a Systolic Array Based Neural Network Accelerator

11 February 2018
Jeff Zhang
Tianyu Gu
K. Basu
S. Garg
ArXivPDFHTML

Papers citing "Analyzing and Mitigating the Impact of Permanent Faults on a Systolic Array Based Neural Network Accelerator"

11 / 11 papers shown
Title
Periodic Online Testing for Sparse Systolic Tensor Arrays
Periodic Online Testing for Sparse Systolic Tensor Arrays
C. Peltekis
Chrysostomos Nicopoulos
G. Dimitrakopoulos
52
0
0
25 Apr 2025
Understanding Silent Data Corruption in LLM Training
Understanding Silent Data Corruption in LLM Training
Jeffrey Ma
Hengzhi Pei
Leonard Lausen
George Karypis
42
0
0
17 Feb 2025
FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN
  Accelerators through Fault-Aware Quantization
FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN Accelerators through Fault-Aware Quantization
Muhammad Abdullah Hanif
Muhammad Shafique
AAML
39
2
0
21 May 2023
A Systematic Literature Review on Hardware Reliability Assessment
  Methods for Deep Neural Networks
A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks
Mohammad Hasan Ahmadilivani
Mahdi Taheri
J. Raik
Masoud Daneshtalab
M. Jenihhin
37
25
0
09 May 2023
Improving Reliability of Spiking Neural Networks through Fault Aware
  Threshold Voltage Optimization
Improving Reliability of Spiking Neural Networks through Fault Aware Threshold Voltage Optimization
Ayesha Siddique
K. A. Hoque
27
5
0
12 Jan 2023
Statistical Modeling of Soft Error Influence on Neural Networks
Statistical Modeling of Soft Error Influence on Neural Networks
Haitong Huang
Xing-xiong Xue
Cheng Liu
Ying Wang
Tao Luo
Long Cheng
Huawei Li
Xiaowei Li
29
7
0
12 Oct 2022
Special Session: Towards an Agile Design Methodology for Efficient,
  Reliable, and Secure ML Systems
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems
Shail Dave
Alberto Marchisio
Muhammad Abdullah Hanif
Amira Guesmi
Aviral Shrivastava
Ihsen Alouani
Muhammad Shafique
34
13
0
18 Apr 2022
Fault-Tolerant Deep Learning: A Hierarchical Perspective
Fault-Tolerant Deep Learning: A Hierarchical Perspective
Cheng Liu
Zhen Gao
Siting Liu
Xuefei Ning
Huawei Li
Xiaowei Li
43
9
0
05 Apr 2022
ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks
  considering Unreliable Memories
ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories
Rachmad Vidya Wicaksana Putra
Muhammad Abdullah Hanif
Muhammad Shafique
26
36
0
23 Aug 2021
Robust Machine Learning Systems: Challenges, Current Trends,
  Perspectives, and the Road Ahead
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead
Muhammad Shafique
Mahum Naseer
T. Theocharides
C. Kyrkou
O. Mutlu
Lois Orosa
Jungwook Choi
OOD
81
100
0
04 Jan 2021
ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error
  Resilience for Energy Efficient Deep Neural Network Accelerators
ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Neural Network Accelerators
Jeff Zhang
Kartheek Rangineni
Zahra Ghodsi
S. Garg
36
117
0
11 Feb 2018
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