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 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.