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researcher

M. Weiland

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.DC2
  • cs.PF1
  • cs.SE1

identity via Semantic Scholar / OpenAlex

most citedA highly scalable Met Office NERC Cloud model

23 citations · 35 across the 3 of their papers we have counts for

collaborators

4 papers

cs.DC2020★ 10 cited

A directive based hybrid Met Office NERC Cloud model

Nick Brown, Angus Lepper, Michèle Weiland +3

Large Eddy Simulation is a critical modelling tool for the investigation of atmospheric flows, turbulence and cloud microphysics. The models used by the UK atmospheric research com…

cs.SE2020★ 23 cited

A highly scalable Met Office NERC Cloud model

Nick Brown, Michèle Weiland, Adrian Hill +4

Large Eddy Simulation is a critical modelling tool for scientists investigating atmospheric flows, turbulence and cloud microphysics. Within the UK, the principal LES model used by…

cs.PF2020

Investigating Applications on the A64FX

Adrian Jackson, Michèle Weiland, Nick Brown +2

The A64FX processor from Fujitsu, being designed for computational simulation and machine learning applications, has the potential for unprecedented performance in HPC systems. In…

cs.DC2019★ 2 cited

Evaluating the Arm Ecosystem for High Performance Computing

Adrian Jackson, Andrew Turner, Michele Weiland +3

In recent years, Arm-based processors have arrived on the HPC scene, offering an alternative the existing status quo, which was largely dominated by x86 processors. In this paper,…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.