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비정상 ECG 진단의 에너지 효율적인 재구성 가능한 가속을 위한 OpenCL 기반 FPGA-GPU 혼합 계층 적응 처리 알고리즘 할당.
- Source :
- Journal of the Korea Institute of Information & Communication Engineering; Oct2021, Vol. 25 Issue 10, p1279-1286, 8p
- Publication Year :
- 2021
-
Abstract
- The electrocardiogram (ECG) signal is a good indicator for early diagnosis of heart abnormalities. The ECG signal has a different reference normal signal for each person. And it requires lots of data to diagnosis. In this paper, we propose an adaptive OpenCL-based FPGA-GPU hybrid-layer platform to efficiently accelerate ECG signal diagnosis. As a result of diagnosing 19870 number of ECG signals of MIT-BIH arrhythmia database on the platform, the FPGA accelerator takes 1.15s, that the execution time was reduced by 89.94% and the power consumption was reduced by 84.0% compared to the software execution. The GPU accelerator takes 1.87s, that the execution time was reduced by 83.56% and the power consumption was reduced by 62.3% compared to the software execution. Although the proposed FPGA-GPU hybrid platform has a slower diagnostic speed than the FPGA accelerator, it can operate a flexible algorithm according to the situation by using the GPU. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Korean
- ISSN :
- 22344772
- Volume :
- 25
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- Journal of the Korea Institute of Information & Communication Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 153768573
- Full Text :
- https://doi.org/10.6109/jkiice.2021.25.10.1279