The design and evaluation of a high-performance earth science database
Parallel Computing - Special issues on applications: parallel data servers and applications
A parallel h-adaptive finite element model for atmospheric transport prediction
Advances in Engineering Software - Special issue; special issue on large-scale analysis and design on high-performance computers and workstations
MPI: The Complete Reference
Titan: A High-Performance Remote Sensing Database
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Performance Evaluation of Matrix Solvers on Compaq Alpha and Intel Itanium Processors
PDPTA '02 Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications - Volume 3
Parallel Seismic Ray Tracing in a Global Earth Model
PDPTA '02 Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications - Volume 3
Parallelization of Seismic Wave Calculation by Impulse Response Functions
PDPTA '02 Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications - Volume 3
Concurrent Edge Detection Algorithm Based on Spiral Architecture Using Linux
PDPTA '02 Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications - Volume 1
Large-Scale CFD Data Handling in a VR-Based Otorhinolaryngological CAS-System using a Linux-Cluster
The Journal of Supercomputing
Parallel Compositional Reservoir Simulation on Clusters of PCs
International Journal of High Performance Computing Applications
An Introduction to PC Clusters for High Performance Computing
International Journal of High Performance Computing Applications
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
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This paper discusses an approach that implements a parallel processing of 3-D Prestack Kirchhoff Time Migration (PKTM) on a low-cost PC Cluster by using the Message Passing Interface (MPI), and analyses its performance using a real seismic data as examples. The PC Cluster provides a significant acceleration of the migration processing with the exact same image quality. The ratio between the communication time and processing time is a critical indicator for determining the efficiency of the PC Cluster. If the processing time is longer than the communication time, using more CPUs can efficiently reduce the elapsed time. On the contrary, using more CPUs cannot reduce the elapsed time. Appling this approach to the Alba dataset on our PC Cluster up to 15 CPUs, the elapsed time of PKTM is inversely proportional to the number of CPUs used. The elapsed time for migrating a 2-D seismic line is reduced from 15h using one CPU to 1h using 15 CPUs. The elapsed time for migrating a 3-D image is reduced from 630h using one CPU to 42h using 15 CPUs. Further reduction can be achieved by using more CPUs. However, an optimal CPU number is expected for an application on large PC clusters with hundreds of nodes. Adapting existing algorithms to the cluster environment offers the potential to allow the application of more accurate algorithms for PKTM to construct a more accurate image. This work has proven that the PC Cluster is a powerful and scalable computing resource for oil and gas exploration organizations.