1887

Abstract

MapReduce is a famous programming model for processing large data sets on clusters of computers. However, for pre-stack depth migration (PreSDM), which is a classic migration imaging method in geophysical domain, it shows great inadaptation due to the computational characteristics of the problem. In this paper, an improved programming model is introduced especially designed for Kirchhoff PreSDM and a Data-ware scheduling policy is considered to maximized the utilization of computational and I/O capacities of GPU grid. The implemented framework is tested on actual examples and results show the effectiveness of our model and strategy in comparison with Apache Hadoop which is a popular free implementation of Mapreduce.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.20130649
2013-06-10
2022-01-19
Loading full text...

Full text loading...

http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20130649
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error