Run the Case on Inductiva

Running the Simulation

The following Python script runs the simulation for the 2021 Spring deployment. Save the following code as a .py file before running it.

"""Delft3D Simulation."""
import inductiva

# Allocate a machine on Google Cloud Platform
cloud_machine = inductiva.resources.MachineGroup( \
    provider="GCP",
    machine_type="c2d-highcpu-32",
    spot=True)

# Initialize the Simulator
delft3d = inductiva.simulators.Delft3D(\
    version="6.04.00")

# Run simulation
task = delft3d.run( \
    input_dir="/Path/to/Spring2021_Delft3D_setup",
    commands = ["mpirun -np 32 d_hydro.exe config_d_hydro.xml"],
    on=cloud_machine)

# Wait for the simulation to finish and download the results
task.wait()
cloud_machine.terminate()

task.download_outputs()

task.print_summary()

In this example, we use a c2d-highcpu-32 machine with 32 virtual CPUs. Its performance is slightly better than a high-end desktop. You can explore the full range of available machines here.

Note: Setting spot=True enables the use of spot machines, which are available at substantial discounts. However, your simulation may be interrupted if the cloud provider reclaims the machine.

When the simulation is complete, we terminate the machine, download the results and print a summary of the simulation as shown below.

Task status: Success

Timeline:
    Waiting for Input         at 22/10, 09:15:47      1.742 s
    In Queue                  at 22/10, 09:15:49      41.202 s
    Preparing to Compute      at 22/10, 09:16:30      3.284 s
    In Progress               at 22/10, 09:16:33      64214.631 s
        └> 64214.365 s     mpirun -np 32 d_hydro.exe config_d_hydro.xml
    Finalizing                at 23/10, 03:06:48      214.477 s
    Success                   at 23/10, 03:10:22

Data:
    Size of zipped output:    5.68 GB
    Size of unzipped output:  18.34 GB
    Number of output files:   64

Total estimated cost (US$): 2.79 US$
    Estimated computation cost (US$): 2.78 US$
    Task orchestration fee (US$): 0.010 US$

Note: A per-run orchestration fee (0.010 US$) applies to tasks run from 01 Dec 2025, in addition to the computation costs.
Learn more about costs at: https://inductiva.ai/guides/how-it-works/basics/how-much-does-it-cost

As you can see in the "In Progress" line, the part of the timeline that represents the actual execution of the simulation, the core computation time of this simulation was approximately hours.

To run the 2021 Fall deployment, simply update the input_dir parameter accordingly.

Scaling Up Your Simulation

Scaling up is simple: either increase the number of vCPUs by choosing a larger machine_type (e.g., from c2d-highcpu-32 to c2d-highcpu-56) or switch to a machine from the latest-generation c4d series. Both approaches can significantly reduce runtime.

⚠️ Important: If you change the number of vCPUs, be sure to update the mpirun command accordingly (e.g., -np 56) to match your machine configuration.

Below are the results of running the 2021 Spring deployment across different computational setups:

As shown above, increasing the number of vCPUs or switching to newer-generation machines leads to a clear reduction in runtime, though at a higher computational cost. The optimal setup depends on your priorities, whether minimizing time-to-results or optimizing cost-efficiency. The Inductiva platform makes it easy to explore this trade-off, enabling you to scale Delft3D simulations seamlessly across different compute configurations.