Efficient load balancing and data remapping for adaptive grid calculations
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
HARP: a fast spectral partitioner
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
Global load balancing with parallel mesh adaption on distributed-memory systems
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Wavefront Diffusion and LMSR: Algorithms for Dynamic Repartitioning of Adaptive Meshes
IEEE Transactions on Parallel and Distributed Systems
A compilation method for communication—efficient partitioning of DOALL loops
Compiler optimizations for scalable parallel systems
Journal of Parallel and Distributed Computing
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The computational requirements for an adaptive solution of unsteady problems change as the simulation progresses. This causes workload imbalance among processors on a parallel machine which, in turn, requires significant data movement at runtime. We present a new dynamic load-balancing framework, called JOVE, that balances the workload across all processors with a global view. Whenever the computational mesh is adapted, JOVE is activated to eliminate the load imbalance. JOVE has been implemented on an IBM SP2 distributed-memory machine in MPI for portability. Experimental results for two model meshes demonstrate that mesh adaption with load balancing gives more than a sixfold improvement over one without load balancing. We also show that JOVE gives a 24-fold speedup on 64 processors compared to sequential execution.