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Test Your Inductiva Setup

Test your Inductiva.AI setup by running a quick CaNS simulation in the cloud before moving on to large-scale CFD simulations.

Before diving into tutorials and benchmarks, let's ensure that your Inductiva Python package is properly set up. To confirm everything is working as expected, simply run a quick CaNS simulation — it only takes a few seconds!

Step 1: Copy and Run the Code

Copy the code below and save it as example.py on your Desktop (or in your preferred directory).

"""CaNS example"""
import inductiva

# Allocate cloud machine on Google Cloud Platform
cloud_machine = inductiva.resources.MachineGroup( \
    provider="GCP",
    machine_type="c2d-highcpu-4",
    spot=True)

# Download the input files into a folder
input_dir = inductiva.utils.download_from_url(
    "https://storage.googleapis.com/inductiva-api-demo-files/"
    "cansv2.4.0-input-example.zip",
    unzip=True)

# Initialize the Simulator
cans = inductiva.simulators.CaNS(\
    version="2.4.0")

# Run simulation
task = cans.run(input_dir=input_dir,
    sim_config_filename="input.nml",
    on=cloud_machine)

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

task.download_outputs()

task.print_summary()

Open your command line, then navigate to the Desktop by running:

cd ~/Desktop

Execute the Python script by running:

python example.py

Note: On some systems, you might need to use python3 instead of python.

All the necessary simulation artifacts and configuration files will be automatically downloaded to your computer. The CaNS simulation will then be sent to a cloud machine for execution.

Step 2: Verify the Task Status

After the simulation completes, a task summary will be displayed in your terminal, as shown below.

Task status: Success

Timeline:
    Waiting for Input         at 13/06, 13:35:57      0.649 s
    In Queue                  at 13/06, 13:35:58      38.191 s
    Preparing to Compute      at 13/06, 13:36:36      1.691 s
    In Progress               at 13/06, 13:36:38      4.506 s
        ├> 1.184 s         mkdir -p data
        └> 3.125 s         /opt/openmpi/4.1.6/bin/mpirun --np 0 --use-hwthread-cpus cans input.nml
    Finalizing                at 13/06, 13:36:42      0.458 s
    Success                   at 13/06, 13:36:43

Data:
    Size of zipped output:    661.22 KB
    Size of unzipped output:  2.40 MB
    Number of output files:   269

Total estimated cost (US$): 0.010057 US$
    Estimated computation cost (US$): 0.000057 US$
    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/basics/how-much-does-it-cost

If the task status shows Success, congratulations! You've successfully run an CaNS simulation.

This simple example tested your installation on a small machine with just 4 virtual CPUs. Inductiva offers far more powerful options to supercharge your simulations.

Start running simulations seamlessly!

Need Help?

If you encounter any issues or need further assistance, don't hesitate to Contact Us. We're here to help!

Versions and Containers

Explore supported CaNS versions and container images on the Inductiva.AI Cloud HPC platform.

Run Your First Simulation

Step-by-step guide to run your first CaNS simulation on Inductiva.AI. Easily launch, monitor and analyse results.