Interpretive performance prediction for parallel application development
Journal of Parallel and Distributed Computing
Compile-Time Performance Prediction of HPF/Fortran 90D
IEEE Parallel & Distributed Technology: Systems & Technology
Adaptive Runtime Partitioning of AMR Applications on Heterogeneous Clusters
CLUSTER '01 Proceedings of the 3rd IEEE International Conference on Cluster Computing
On Partitioning Dynamic Adaptive Grid Hierarchies
HICSS '96 Proceedings of the 29th Hawaii International Conference on System Sciences Volume 1: Software Technology and Architecture
Engineering a Distributed Computational Collaboratory
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 9 - Volume 9
Forecasting network performance to support dynamic scheduling using the network weather service
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
A Hierarchical Analysis Approach for High Performance Computing and Communication Applications
HICSS '99 Proceedings of the Thirty-Second Annual Hawaii International Conference on System Sciences-Volume 3 - Volume 3
Engineering an autonomic partitioning framework for Grid-based SAMR applications
High performance scientific and engineering computing
Investigating autonomic runtime management strategies for SAMR applications
International Journal of Parallel Programming - Special issue: The next generation software program
Enabling scalable parallel implementations of structured adaptive mesh refinement applications
The Journal of Supercomputing
SpringSim '07 Proceedings of the 2007 spring simulation multiconference - Volume 2
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This paper presents the design, prototype implementation, and evaluation of a runtime management framework for structured adaptive mesh refinement applications. The framework is capable of reactively and proactively managing and optimizing application execution using current system and application state, predictive models for system behavior and application performance, and an agent based control network. The overall goal of this research is to enable large-scale dynamically adaptive scientific and engineering simulations on distributed, heterogeneous and dynamic execution environments such as the computational "grid".