PLUM: parallel load balancing for adaptive unstructured meshes
Journal of Parallel and Distributed Computing
Fluids in the universe: adaptive mesh refinement in cosmology
Computing in Science and Engineering
A unified algorithm for load-balancing adaptive scientific simulations
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
A common data management infrastructure for adaptive algorithms for PDE solutions
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
An Application-Centric Characterization of Domain-Based SFC Partitioners for Parallel SAMR
IEEE Transactions on Parallel and Distributed Systems
Dynamic Load Balancing for Structured Adaptive Mesh Refinement Applications
ICPP '02 Proceedings of the 2001 International Conference on Parallel Processing
An Evaluation of Partitioners for Parallel SAMR Applications
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Run-time Optimisation of Grid Workflow Applications
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Grid-Enabling SPMD Applications through Hierarchical Partitioning and a Component-Based Runtime
Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
Hi-index | 0.00 |
Distributed structured adaptive mesh refinement (SAMR) techniques offer the potential for accurate and cost-effective solutions of physically realistic models of complex physical phenomena. However, the heterogeneous and dynamic nature of SAMR applications results in significant runtime management challenges. This paper investigates autonomic application-sensitive SAMR runtime management strategies and presents the design, implementation, and evaluation of ARMaDA, a self-adapting and optimizing partitioning framework for SAMR applications. ARMaDA monitors and characterizes application runtime state, and dynamically selects and invokes appropriate partitioning mechanisms that match current SAMR state and optimize its computational and communication performance. The advantages of the autonomic partitioning capabilities provided by ARMaDA are experimentally demonstrated.