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Performance improvements and rapid research computing deployments with WRF on Google Cloud

This post was from a previous version of the WRF&MPAS-A Support Forum. New replies have been disabled and if you have follow up questions related to this post, then please start a new thread from the forum home page.

We have published an article discussing a benchmarking study of WRF on Google Cloud Platform.

Fluid Numerics Journal - WRF v4 on Google Cloud

We show that optimal performance is currently achieved using the c2 GCE machine types with optimal cost-performance achieved by subscribing MPI ranks to each vCPU (hyperthread). Additionally, we demonstrate clear advantages of using WRF’s asynchronous parallel IO option in combination with a Lustre file system hosted on GCP over single-point NFS file-server solutions. For the WRF CONUS 12km benchmark, we show how disabling hyperthreading produces comparable results to MPI+OpenMP configurations when the minimum domain size per rank is reached. For the WRF CONUS 2.5km benchmark, we’ll present scaling efficiency results out to 7,680 ranks on Google Cloud Platform.

The result of this study includes artifacts that allow others to reproduce these results as well as quickly get started with WRF on Google Cloud. Specifically, this includes a click-to-deploy RCC-WRF solution as well as open-source VM image baking scripts on

Happy to field comments and questions in reply to this post.