Parallel computing method for HRV time-domain based on GPU

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Abstract

HRV (Heart rate variability, which has a function of prediction for cardiovascular disease) contains a wealth of medical information, rapid extraction and procession of these signals will bring an important meaning for the prevention of heart diseases. Physionet open source project provides a good platform for the research and development of HRV, which also provides demonstration tools for the calculation of HRV. The characteristics of medical signal are real-time and have large volume of data. Conventional serial methods are difficult to meet the requirements of biomedicine, and the parallel method based on multi-core CPU is larger communication overhead. In this paper, we designed some parallel algorithms for the calculation of HRV in time-domain based on the strategy of parallel reduction, compared and analyzed the various optimization methods, and received the highest 38 times speedup compared with serial method.

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Wang, J., Chen, W., & Hou, G. (2015). Parallel computing method for HRV time-domain based on GPU. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9529, pp. 434–443). Springer Verlag. https://doi.org/10.1007/978-3-319-27122-4_30

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