For a large class of irregular grid applications, the computational structure of the problem changes in an incremental fashion from one phase of the computation to another. Eventually, as the graph evolves, it becomes necessary to correct the partition in accordance with the structural changes in the computation. Two diierent types of schemes to accomplish this task have been developed recently...

As scientific data sets grow exponentially in size, the need for scalable algorithms that heuristically partition the data increases. In this paper, we describe the threestep evolution of a hierarchical partitioning algorithm for large-scale spatio-temporal scientific data sets generated by massive simulations. The first version of our algorithm uses a simple top-down partitioning technique, wh...

Main characteristics of desktop grids are the large number of nodes and their heterogeneity. Application speedup on a large-scale desktop grid is limited by the heterogeneous computational capabilities of each node, which increase the synchronization overhead, and by the large number of nodes, that results in the serial fraction dominating performance. In this paper we present an innovative tec...

The overset grid methodology has significantly reduced time-to-solution of highfidelity computational fluid dynamics (CFD) simulations about complex aerospace configurations. The solution process resolves the geometrical complexity of the problem domain by using separately generated but overlapping structured discretization grids that periodically exchange information through interpolation. How...

Grid computing allows the usage of distributed resources possibly belonging to different institutions in a transparent way. This paper presents InteGrade, an object-oriented Grid tool that focuses on leveraging the idle computing power of shared desktop machines. Moreover, it currently allows the execution of sequential, parametric, and BSP parallel applications.

SpatialHadoop is an extended MapReduce framework that supports global indexing that spatial partitions the data across machines providing orders of magnitude speedup, compared to traditional Hadoop. In this paper, we describe seven alternative partitioning techniques and experimentally study their effect on the quality of the generated index and the performance of range and spatial join queries...

This paper describes the methods that can be used to detect building objects under the circumstances of high object density and scene complexity seen in 1-metre high resolution satellite imagery. In order to reduce the building hypothesis space in early processes, a local Fourier analysis does an analysis of the dominant orientation angle in a building cluster. This serves to extract the focuse...

We present an implementation of a finite-difference approximation for the solution of partial differential equations on transputer networks. The grid structure associated with the finite-difference approximation is exploited by using geometric partitioning of the data among the processors. This provides a very low degree of communication between the processors. The resultant system of linear eq...