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Parallelization of Noise Reduction Algorithm for Seismic Data on a Beowulf Cluster


Izzatdin Aziz, Thayalan Sandran, Nazleeni Haron, Mohd Hilmi Hasan, Mazlina Mehat


Vol. 10  No. 1  pp. 96-106


This paper presents the parallelization of a sequential noise reduction algorithm for seismic data processing into a parallel algorithm. The parallel algorithm was developed using C language with the utilization of the Message Passing Interface (MPI) library. The proposed algorithm has been implemented on an experimental Beowulf cluster which consists of 12 nodes operating on Linux Ubuntu platform. The system was tested with various test scenarios to gauge its performance. Based on the results obtained, it can be concluded that parallel implementation of the noise reduction algorithm has significantly reduced the processing time.


Beowulf cluster, Fast Fourier Transform, F-k Filter, MPI, Parallel Programming