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The parallelization of convolution on a CNN using a SIMT based GPGPU
Ist Teil von
2016 International SoC Design Conference (ISOCC), 2016, p.333-334
Ort / Verlag
IEEE
Erscheinungsjahr
2016
Link zum Volltext
Quelle
IEEE/IET Electronic Library (IEL)
Beschreibungen/Notizen
This paper proposes a method to accelerate convolutional neural network(CNN) by utilizing GPGPU. The convolutional layer of the conventional CNN required a large number of multiplication operations. This paper seeks to reduce the number of multiplication operations through Winograd convolution operation and perform parallel processing of the convolution operation by utilizing SIMT structure of GPGPU. The experiment was conducted using ModelSim and TestDrive, and the experimental results showed that the processing time was improved by about 7%, compared to the conventional convolution operation.