Fault and Delay Tolerance in Deep Learning Framework under GPU

Thanasekhar, B; Gomathy, N; Shwetha, B; Sumithra, A

doi:10.1109/icoac48765.2019.246830

Cited by 1 publication

(2 citation statements)

References 23 publications

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“…Architecture framework and strategy [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] Scheduling and communication [26][27][28][29] Image processing and computer vision [30][31][32][33][34][35][36][37][38][39][40] Medical or health [41][42][43][44] Modeling or prediction [45][46][47][48][49][50][51] Convolution or performance analysis [6,[52][53][54] VLSI placement [55] GPU-based Machine Learning Technologies for EI Architecture platform [56][57][58][59]…”

Section: Gpu-based Deep Learning Technologies For Eimentioning

confidence: 99%

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GPU-Based Embedded Intelligence Architectures and Applications

Ang

Seng

2021

Electronics

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This paper present contributions to the state-of-the art for graphics processing unit (GPU-based) embedded intelligence (EI) research for architectures and applications. This paper gives a comprehensive review and representative studies of the emerging and current paradigms for GPU-based EI with the focus on the architecture, technologies and applications: (1) First, the overview and classifications of GPU-based EI research are presented to give the full spectrum in this area that also serves as a concise summary of the scope of the paper; (2) Second, various architecture technologies for GPU-based deep learning techniques and applications are discussed in detail; and (3) Third, various architecture technologies for machine learning techniques and applications are discussed. This paper aims to give useful insights for the research area and motivate researchers towards the development of GPU-based EI for practical deployment and applications.

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Section: Gpu-based Deep Learning Technologies For Eimentioning

confidence: 99%

“…The authors in [53] proposed a fault-tolerant approach with soft errors as faults in the network and introduced triple modular redundancy to detect and rectify the faults. Their work showed that the presence of faults in the network would cause a significant decrease in the accuracy of the network.…”

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confidence: 99%

GPU-Based Embedded Intelligence Architectures and Applications

Ang

Seng

2021

Electronics

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show abstract

Fault and Delay Tolerance in Deep Learning Framework under GPU

Cited by 1 publication

References 23 publications

GPU-Based Embedded Intelligence Architectures and Applications

GPU-Based Embedded Intelligence Architectures and Applications

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