Delft3D FM is an engine for hydrodynamical simulations on unstructured grids in 1D-2D-3D. It is the successor of Delft3D-FLOW and SOBEK-FLOW.
Running your Delft3D FM workload on Nerdalize
Delft3D FM is currently in private beta. Would you like to run large simulations with Delft3D FM? Let us know if you would like beta access.
The following steps assume you’ve been given access to the private beta and have credentials on-hand that provide access to the Delft3D FM image repository.
Make sure you’ve set up Nerd, our CLI.
Set up your dataset.
Download our example dataset and unzip it.
Alternatively you can use your own dataset, for which this README explains the required dataset structure.
Upload your dataset.
$ nerd dataset upload --name=dflowfm-input path-to-data-folder
Archiving (Step 1/2): 89.63 KB / 89.63 KB [=======] 100.00% 0s Uploading (Step 2/2): 109.57 KB / 109.57 KB [=======] 100.00% 0s Uploaded dataset: 'dflowfm-input' To run a job with a dataset, use: 'nerd job run'
Start Delft3D FM while providing credentials to use the private image.
Nerd will ask for your credentials to gain access to the private image. Note that your password will be hidden while you type it.
$ nerd job run \ --private \ --name=dflowfm-run \ --input=dflowfm-input:/data \ --output=dflowfm-output:/output \ nerdalize/dflowfm Please provide credentials for the Docker Hub repository that stores the private image: Username: <your_username> Password: <your_password>
Submitted job: 'dflowfm-run' To see whats happening, use: 'nerd job list'
Check on the status of your job.
$ nerd job list
JOB IMAGE INPUT OUTPUT MEMORY VCPU CREATED AT PHASE DETAILS dflowfm-run deltares/delft3dfm dflowfm-input dflowfm-output 3.0 2.0 6 seconds ago Running
When your task’s status is
Completedit’s finished and you can continue to download the output.
If you want to review the log output, run:
$ nerd job logs dflowfm-run
Download the collection of output files.
$ nerd dataset download dflowfm-run ~/my-delft3dfm-output
Downloading (Step 1/2): 117.13 MB / 117.13 MB [=======] 100.00% 0s Unarchiving (Step 2/2): 117.13 MB / 117.13 MB [=======] 100.00% 0s Downloaded 1 dataset