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Parallel Computation Algorithm (PCA) for Large Geophysical Processes

Adewale Amosu
Center for Earthquake Research and Information, Memphis, TN

Over the past decade, the world of Geophysics has seen a tremendous increase in collection, distribution of Geophysical data. With such large amounts of data available for several geophysical studies, end users run into problems with limited computational resources and computational power. I have developed an algorithm that skillfully manages processing flow of large job within the limits of available computational power.

Written in C and C++, PCA is able to control and schedule the running of independent processes in parallel. A Java based interface is also been developed. PCA is able to run in limited storage space by storing the output produced on an external email server. Development and testing has been carried out in UNIX and is being extended to other commonly platforms.

The functionality of PCA is demonstrated in using it to convolve large array of 2D displacement green-­‐functions with loading functions. The fast 2D convolution algorithm is also made available, as convolution is one of the core processes widely used in Geophysics.

AAPG Search and Discovery Article #90182©2013 AAPG/SEG Student Expo, Houston, Texas, September 16-17, 2013