A Case of Parallel EEG Data Processing upon a Beowulf Cluster

Electroencephalogram (EEG) data processing applications have become routine tasks in both bioscience and neuroscience research, which are usually highly compute and data intensive. In this paper, we present a parallel method to analyze the huge EEG data with a Beowulf cluster. Through an example of...

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Bibliographic Details
Published in2009 15th International Conference on Parallel and Distributed Systems pp. 799 - 803
Main Authors Yufeng Yao, Jinyi Chang, Kaijian Xia
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Application software
Beowulf Cluster
Bioinformatics
Concurrent computing
Data processing
Distributed computing
Electroencephalography
Local area networks
Message passing
MPI
Neuroinformatics
Neuroscience
Parallel and Distributed Computing
Parallel processing
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Summary:Electroencephalogram (EEG) data processing applications have become routine tasks in both bioscience and neuroscience research, which are usually highly compute and data intensive. In this paper, we present a parallel method to analyze the huge EEG data with a Beowulf cluster. Through an example of the synchronization measurement of multiple neuronal populations, the procedure of exploiting the parallelism of EEG data processing applications to achieve speed-up has been detailed. The experimental results indicate that the execution efficiency of EEG data processing can be improved dramatically using parallel and distributed computing techniques even with inexpensive computing platform.
ISBN:9781424457885
1424457882
ISSN:1521-9097
2690-5965
DOI:10.1109/ICPADS.2009.65