Exploring Winograd Convolution for Cost-Effective Neural Network Fault Tolerance-Reference-Cited by-同舟云学术

Exploring Winograd Convolution for Cost-Effective Neural Network Fault Tolerance

Published:2023-11 Issue:11 Volume:31 Page:1763-1773
ISSN:1063-8210
Container-title:IEEE Transactions on Very Large Scale Integration (VLSI) Systems
language:
Short-container-title:IEEE Trans. VLSI Syst.

Author:

Xue Xinghua¹^ORCID,Liu Cheng¹^ORCID,Liu Bo²,Huang Haitong¹^ORCID,Wang Ying¹^ORCID,Luo Tao³^ORCID,Zhang Lei¹,Li Huawei¹^ORCID,Li Xiaowei¹^ORCID

Affiliation:

1. State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

2. Beijing Institute of Control Engineering, Beijing, China

3. Institute of High Performance Computing, A*STAR, Fusionopolis, Singapore

Funder

National Natural Science Foundation of China

Space Trusted Computing and Electronic Information Technology Laboratory of Beijing Institute of Control Engineering

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Link

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2. Exploring the Behavior of Soft-Error Rate Reduction Algorithms in Digital Circuits;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

3. Microarchitecturally Exploring Fault-Tolerance and Timing on Silicon on Chip;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

4. Reliable Fault Tolerance and Recovery for VLSI Systems;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

5. Soft Error Reliability Analysis of Vision Transformers;IEEE Transactions on Very Large Scale Integration (VLSI) Systems;2023-12