2022
DOI: 10.1007/s11227-022-04399-2
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Heterogeneous gradient computing optimization for scalable deep neural networks

Abstract: Nowadays, data processing applications based on neural networks cope with the growth in the amount of data to be processed and with the increase in both the depth and complexity of the neural networks architectures, and hence in the number of parameters to be learned. High-performance computing platforms are provided with fast computing resources, including multi-core processors and graphical processing units, to manage such computational burden of deep neural network applications. A common optimization techni… Show more

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Cited by 3 publications
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