Abstract
In this paper, we consider the parallel implementation of a block Cholesky factorization based on a nested dissection ordering for unstructured problems. We focus on loosely coupled networks of many processors with local memory and message passing mechanism. More precisely, we study a parallel block solver associated with refined partitions from the separator partition; the aim is to find the partition corresponding to the correct granularity leading to a high quality mapping (in terms of load balancing for the processors, of average length for the routing paths, and of average edge contention on the network). Then, we propose a refinement algorithm leading to this good granularity, and we provide some numerical measurements using the mapping tool included in the ADAM environment.
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Charrier, P., Roman, J. (1992). Partitioning and mapping for parallel nested dissection on distributed memory architectures. In: Bougé, L., Cosnard, M., Robert, Y., Trystram, D. (eds) Parallel Processing: CONPAR 92—VAPP V. VAPP CONPAR 1992 1992. Lecture Notes in Computer Science, vol 634. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55895-0_424
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DOI: https://doi.org/10.1007/3-540-55895-0_424
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