Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
The Legion vision of a worldwide virtual computer
Communications of the ACM
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Multivariate geographic clustering in a metacomputing environment using Globus
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
MPICH-G2: a Grid-enabled implementation of the Message Passing Interface
Journal of Parallel and Distributed Computing - Special issue on computational grids
High-resolution remote rendering of large datasets in a collaborative environment
Future Generation Computer Systems - iGrid 2002
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Application of grid computing to parameter sweeps and optimizations in molecular modeling
Future Generation Computer Systems
The Cambridge CFD grid for large-scale distributed CFD applications
Future Generation Computer Systems
Enabling interactive and collaborative oil reservoir simulations on the Grid: Research Articles
Concurrency and Computation: Practice & Experience - High-Performance Computing in Geosciences
Cross-Site Computations on the TeraGrid
Computing in Science and Engineering
A problem solving environment for multidisciplinary coupled simulations in computational grids
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
Simulating and visualizing the human arterial system on the TeraGrid
Future Generation Computer Systems - IGrid 2005: The global lambda integrated facility
Grid computing for parallel bioinspired algorithms
Journal of Parallel and Distributed Computing - Special issue on parallel bioinspired algorithms
Electron tomography of complex biological specimens on the Grid
Future Generation Computer Systems
Solving simulation optimization problems on grid computing systems
Parallel Computing - Optimization on grids - Optimization for grids
Runtime Visualization of the Human Arterial Tree
IEEE Transactions on Visualization and Computer Graphics
Grid solutions for biological and physical cross-site simulations on the teragrid
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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Grid-computing environments are becoming increasingly popular for scientific computing due to the significant increase in capacity that they represent when compared to a single computational resource (e.g., a single cluster), their ubiquitous availability and advances in grid middleware components. Several such specialized grid environments are now available for users in the commercial and research sectors. One such effort for research is the TeraGrid, consisting of a collection of geographically distributed heterogeneous supercomputer resources including data storage resources. Parallel implementations for these environments are inherently multilevel and obtaining efficient mapping of work to processors can be eXtremely challenging. This paper eXtends an eXisting MPI application to the grid via the use of grid-enabled MPI libraries. The application uses a simulation-optimization framework involving coarse-grained parallelism in the optimizer and fine-grained parallelism in the finite-element-based simulator. Using parallelism at both these levels is essential for problems involving computationally intensive simulation steps. A hierarchical grid architecture consisting of a collection of supercomputers is ideally suited for these types of problems as a good application-to-architecture mapping can be obtained with a proper implementation. This paper presents the performance results of our implementation on the TeraGrid network consisting of three geographically distributed supercomputers.