Difference between revisions of "WRF on the Cloud"
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| − | + | LADCO is seeking to understand the best practices for submitting and managing multiprocessor computing jobs on a cloud computing platform. In particular, LADCO would like to develop a WRF production environment that utilizes cloud-based computing. The goal of this project is to prototype a WRF production environment on a public, on-demand high performance computing service in the cloud to create a WRF platform-as-a-service (PaaS) solution. The WRF PaaS must meet the following objectives: | |
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| + | * Configurable computing and storage to scale, as needed, to meet that needs of different WRF applications | ||
| + | * Configurable WRF options to enable changing grids, simulation periods, physics options, and input data | ||
| + | * Flexible cloud deployment from a command line interface to initiate computing clusters and spawn WRF jobs in the cloud | ||
Revision as of 20:44, 26 November 2018
LADCO is seeking to understand the best practices for submitting and managing multiprocessor computing jobs on a cloud computing platform. In particular, LADCO would like to develop a WRF production environment that utilizes cloud-based computing. The goal of this project is to prototype a WRF production environment on a public, on-demand high performance computing service in the cloud to create a WRF platform-as-a-service (PaaS) solution. The WRF PaaS must meet the following objectives:
- Configurable computing and storage to scale, as needed, to meet that needs of different WRF applications
- Configurable WRF options to enable changing grids, simulation periods, physics options, and input data
- Flexible cloud deployment from a command line interface to initiate computing clusters and spawn WRF jobs in the cloud
