期刊
IEEE DESIGN & TEST
卷 40, 期 2, 页码 75-81出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MDAT.2022.3180977
关键词
Hardware; Circuit faults; Systolic arrays; Computational modeling; Manganese; Artificial intelligence; Tensors; deep neural networks; hardware faults; hardware reliability; fault model; fault tolerance; fault injection; program vulnerability
This article discusses a hardware fault simulation method based on an application program interface (API) to analyze the impact of hardware faults on the failure probability of deep neural network (DNN) accelerators.
Editor 's notes: This article presents an application program interface (API)-based hardware fault simulation method to investigate the effect of hardware faults on the failure probability of deep neural network (DNN) accelerators. -Fei Su, Intel Corporation
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