Impact Of Load Balancing On Unstructured Adaptive Grid Computations For Distributed-Memory Multiprocessors

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 loadbalancing 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.

• Type: Conference
• Year: 1996
• Where: SPDP
• Authors: Andrew Sohn, Rupak Biswas, Horst D. Simon
• Keywords: Distributed And Parallel Computing, JOVE, Load Balancing, SPDP 1996, Workload Imbalance