The AppLeS parameter sweep template: user-level middleware for the grid
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
An automatic design optimization tool and its application to computational fluid dynamics
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Adaptive Computing on the Grid Using AppLeS
IEEE Transactions on Parallel and Distributed Systems
Heuristics for Scheduling Parameter Sweep Applications in Grid Environments
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
High Performance Parametric Modeling with Nimrod/G: Killer Application for the Global Grid?
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
Implementation and utilisation of a Grid-enabled problem solving environment in Matlab
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
Sequential design and rational metamodelling
WSC '05 Proceedings of the 37th conference on Winter simulation
A multi-cluster grid enabled evolution framework for aerodynamic airfoil design optimization
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
H2O metacomputing – jini lookup and discovery
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
User experiences with nuclear physics calculations on a h2o metacomputing system and on the BEgrid
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
EGC'05 Proceedings of the 2005 European conference on Advances in Grid Computing
Generating sequential space-filling designs using genetic algorithms and Monte Carlo methods
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
A novel sequential design strategy for global surrogate modeling
Winter Simulation Conference
A Novel Hybrid Sequential Design Strategy for Global Surrogate Modeling of Computer Experiments
SIAM Journal on Scientific Computing
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Simulating and optimizing complex physical systems is known to be a task of considerable time and computational complexity. As a result, metamodeling techniques for the efficient exploration of the design space have become standard practice since they reduce the number of simulations needed. However, conventionally such metamodels are constructed sequentially in a one-shot manner, without exploiting inherent parallelism. To tackle this inefficient use of resources we present an adaptive framework where modeler and simulator interact through a distributed environment, thus decreasing model generation and simulation turnaround time. This paper provides evidence that such a distributed approach for adaptive sampling and modeling is worthwhile investigating. Research in this new field can lead to even more innovative automated modeling tools for complex simulation systems.