Abstract
Recent advances of experimental methods and neuroscience research have made neural signals constantly massive and analysis of these signals highly compute-intensive. This study explore the possibility proposes a massively parallel approach for analysis of neural signals using General-purpose computing on the graphics processing unit (GPGPU). We demonstrate the uses and correctness of the proposed approach via a case of analyzing EEG with focal epilepsy. An experimental examination has been carried out to investigate (1) the GPGPU-aided approach’s performance and (2) energy costs of the GPGPU-aided application versus the original CPU-only systems. Experimental results indicate that the proposed approach excels in both aspects.
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Chen, D., Lu, D., Tian, M. et al. Towards energy-efficient parallel analysis of neural signals. Cluster Comput 16, 39–53 (2013). https://doi.org/10.1007/s10586-011-0175-6
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DOI: https://doi.org/10.1007/s10586-011-0175-6