Fine-grained Locality-aware Parallel Scheme for Anisotropic Mesh Adaptation | Zendy

Hoby Rakotoarivelo | Zendy; Franck Ledoux | Zendy; Franck Pommereau | Zendy

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Fine-grained Locality-aware Parallel Scheme for Anisotropic Mesh Adaptation

Author(s) -

Hoby Rakotoarivelo,

Franck Ledoux,

Franck Pommereau

Publication year - 2016

Publication title -

procedia engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.32

H-Index - 74

ISSN - 1877-7058

DOI - 10.1016/j.proeng.2016.11.035

Subject(s) - computer science , parallel computing , scalability , locality , graph , scheme (mathematics) , kernel (algebra) , concurrency , node (physics) , distributed computing , load balancing (electrical power) , adaptation (eye) , theoretical computer science , mathematics , database , mathematical analysis , linguistics , philosophy , physics , geometry , structural engineering , optics , combinatorics , engineering , grid

International audienceIn this paper, we provide a fine-grained parallel scheme for anisotropic mesh adaptation on NUMA1 architectures. Data dependencies are expressed by a graph for each kernel, and concurrency is extracted through fine-grained graph coloring. Tasks are structured into bulk-synchronous steps to avoid data races and to aggregate shared-data accesses. To ensure performance prediction, time cost and load imbalance are theoretically characterized. The devised scheme was evaluated on a 4 NUMA node (2-socket) machine, and a mean efficiency of 70% was reached on 32 cores for 3 kernels out of 4. The impact of irregular degree distribution and data layout on scalability is highlighted

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