Parallel Coarse-Grid Treatment in AMG for Coupled Systems

Emans, Maximilian

doi:10.1007/978-3-642-31500-8_37

Cited by 1 publication

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Given that a large percentage of execution time is spent on the latency-bound bottom solve of the multigrid, we also briefly explore a variant of the box agglomeration technique [36] that consolidates boxes to fewer ranks as we coarsen the Fig. 11: a) The sensivity of the multigrid V-cycle to network/injection bandwidth/latency.…”

Section: F Impact Of Box Consolidationmentioning

confidence: 99%

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

P¹,

D²,

P³

et al. 2016

2016 First International Workshop on Communication Optimizations in HPC (COMHPC)

View full text Add to dashboard Cite

Abstract-We introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and execution strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.

show abstract

Section: F Impact Of Box Consolidationmentioning

confidence: 99%