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1.Poster Title

Computational Benefits of an Ensemble-Based Approach to

Climate Modeling and Testing at Scale

2.AuthorsMatthew Norman, Abigail Gaddis (Unlicensed), Valentine Anantharaj, Kate Evans (Unlicensed), Salil Mahajan, Patrick Worley (Unlicensed)
3.GroupAtmosphere, Performance
4.ExperimentN/A
5.Poster CategoryEarly Result
6.Submission Typeposter
7.Poster Linkhttps://acme-climate.atlassian.net/wiki/download/attachments/23200211/ACME_ensembles.pdf

 

Abstract

The status quo for high-resolution climate simulation is to perform a very small ensemble (order five) of long simulations (roughly a century) for various scenarios arising from IPCC specifications. To succeed in feasible time, a throughput constraint of five Simulated model Years Per wallclock Day (SYPD) is generally accepted as necessary. To achieve this, CAM-SE is used and is scaled over many Processing Elements (PEs), and work per node is very small. At this scale, parallel data transfer overheads are 40% of the total runtime or more, and there are very few threadable indices to use on an accelerator (e.g. Graphics Processing Unit, GPU). Also, even at these scaling limits, ACME is barely achieving a “capability-scale” portion of Titan (i.e., > 25% of the machine), and throughput is still only around one SYPD for the 28km-mesh water cycle experiment targeted by ACME. This, in turn, means (1) a low benefit from using GPUs and (2) poor usage of computer allocations, and (3) less likelihood of receiving large computing allocations in the future.

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