Implement deep neuron networks on VPipe parallel system: a ResNet variant implementation

Xinrong Zhu

doi:10.1117/12.2671359

28 April 2023 Implement deep neuron networks on VPipe parallel system: a ResNet variant implementation

Xinrong Zhu

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126104I (2023) https://doi.org/10.1117/12.2671359
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Deep Neuron Networks (DNNs) rapidly develop across numerous industries and fields. The Residual Network (ResNet) is prevalent for its high performance and novel residual network for image classification. One new architecture derived from ResNet, the ResNet-RS, is proving to have higher accuracy while having lower training difficulty. Furthermore, with the growing network depth and expanding training set size, it is vital to apply different parallel methods to the ResNet to improve the training speed. To evaluate the parallel efficiency of the new architecture, this paper made the following efforts: (1) Implemented the ResNet-RS network on VPipe with a two GPU environment, (2) proposed a formal procedure for DNN implementation on VPipe, and (3) compared the top one and top five accuracy, loss, and epoch time of training between an orthodox ResNet and the derived ResNet-RS on VPipe parallel system.

Citation Download Citation

Xinrong Zhu "Implement deep neuron networks on VPipe parallel system: a ResNet variant implementation", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126104I (28 April 2023); https://doi.org/10.1117/12.2671359

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