The parallelization of convolution on a CNN using a SIMT based GPGPU
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 opera...
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| Published in | 2016 International SoC Design Conference (ISOCC) pp. 333 - 334 |
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| Main Authors | , , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.10.2016
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| Subjects | |
| Online Access | Get full text |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Seonghyung Han Kwanho Lee Kwangyeob Lee Heekyeong Jeon |
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| Snippet | This paper proposes a method to accelerate convolutional neural network(CNN) by utilizing GPGPU. The convolutional layer of the conventional CNN required a... |
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| StartPage | 333 |
| SubjectTerms | Acceleration Computers Convolution convolutional neural network gpu Instruction sets neural network Neural networks Parallel processing parallelism Signal processing algorithms |
| Title | The parallelization of convolution on a CNN using a SIMT based GPGPU |
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