Dynamic load balancing for distributed memory multiprocessors
Journal of Parallel and Distributed Computing
A massively parallel adaptive finite element method with dynamic load balancing
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
A new procedure for dynamic adaption of three-dimensional unstructured grids
Applied Numerical Mathematics
Dynamic load balancing in parallel and distributed networks by random matchings (extended abstract)
SPAA '94 Proceedings of the sixth annual ACM symposium on Parallel algorithms and architectures
Dynamic load balancing for the simulation of granular materials
ICS '95 Proceedings of the 9th international conference on Supercomputing
Parallel Implementation of an Adaptive Scheme for 3D Unstructured Grids on the SP2
IRREGULAR '96 Proceedings of the Third International Workshop on Parallel Algorithms for Irregularly Structured Problems
SPDP '96 Proceedings of the 8th IEEE Symposium on Parallel and Distributed Processing (SPDP '96)
Efficient load balancing and data remapping for adaptive grid calculations
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
Topology preserving dynamic load balancing for parallel molecular simulations
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
Simulating Cloth Free-Form Deformation with a Beowulf Cluster
Proceedings of the 9th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
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Dynamic mesh adaption on unstructured grids is a powerful tool for efficiently computing unsteady problems to resolve solution features of interest. Unfortunately, this causes load imbalance among processors on a parallel machine. This paper describes the parallel implementation of a tetrahedral mesh adaption scheme and a new global load balancing method. A huristic remapping algorithm is presented that assigns partitions to processors such that the redistribution cost is minimized. Results indicate that the paralel performance of the mesh adaption code depends on the nature of the adaption region and show a 35.5X speedup on 64 processors when about 35% of the mesh is randomly adapted. For large-scale scientific computations, our load balancing strategy gives almost a sixfold reduction in solver execution times over non-balanced loads. Furthermore, our heuristic remapper yields processor assignments that are less than 3% off the optimal solutions but requries only 1% of the computational time.