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- Dheeraj Bhardwaj, Suhas Phadke, Sudhakar Yerneni

SUMMARY High level of I/O performance is necessary in making use of parallel machines for many scientific applications. In this paper we discuss the I/O requirements of one such application: 3D seismic migration. I/O performance is the bottleneck rather than the computational or communication performance in 3D seismic imaging. For large 3D data volume it is… (More)

- Suhas Phadke, Dheeraj Bhardwaj, Sudhakar Yerneni
- 1998

SUMMARY This paper examines and anlyzes the dynamics of some computationally intensive seismic applications on a parallel computer. Natural divisibility into smaller tasks and localized communication pattern in seismic applications give strong motivation towards its performance on parallel machines. However we focus here on 3D poststack depth migration and… (More)

- Suhas Phadke, Dheeraj Bhardwaj
- Neural Parallel & Scientific Comp.
- 1998

- Dheeraj Bhardwaj, Sudhakar Yerneni, Suhas Phadke
- 2000

SUMMARY Parallel computers are evaluated by measuring their processor and communication speeds. But, for many large-scale applications the I/O performance is the bottleneck rather than the computational or communication performance. 3-D seismic imaging is one of such applications. Seismic data sets, consisting of recorded pressure waves, can be very large,… (More)

SUMMARY Seismic wave modelling algorithms used for calculating the seismic response of a given earth model, require large computational resources in terms of speed and memory. In this paper we describe the PVM (Parallel Virtual Machine) implementation of these algorithms in a distributed computing environment. Both the acoustic and elastic wave modelling… (More)

- Suhas Phadke, Dheeraj Bhardwaj, Sudhakar Yerneni
- 2000

SUMMARY In this paper we describe the MPI (Message Passing Interface) implementation of an algorithm for solving 3D acoustic wave equation. The derivatives are approximated by central differences and the solution is obtained in a distributed computing environment. Numerical solution uses an explicit finite difference scheme, which is second order accurate… (More)

Parallel Processing, the method of having many small tasks solve one large problem, has emerged as a key enabling technology in modern computing. Most seismic problems carry an inherent parallelism and parallel computing is the only way to achieve improvements of several orders of magnitude in computer performance. In this article we have disused the… (More)

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