Objective#

This tutorial will show you how to run an OpenSees simulation using its Tcl interface, using the SmallMP use case available in the OpenSees GitHub repository.

We will also demonstrate Inductiva’s ability to efficiently scale this use case on a more powerful machine.

Prerequisites#

The requirements for this tutorial are minimal. Simply download the input files from here.

Once you have the simulation files, you’re ready to scale your simulations to the Cloud.

Running Your Simulation#

Here is the code required to run an OpenSees simulation using the Inductiva API.

"""OpenSees Simulation."""
import inductiva

# Instantiate machine group
cloud_machine = inductiva.resources.MachineGroup( \
    provider="GCP",
    machine_type="c2-standard-4")

# Initialize the Simulator
opensees = inductiva.simulators.OpenSees( \
    interface="tcl",
    version="3.7.1")

# Run simulation
task = opensees.run( \
    input_dir="/Path/to/SmallMP",
    sim_config_filename="Example.tcl",
    n_vcpus=4,
    use_hwthread=True,
    on=cloud_machine)

task.wait()
cloud_machine.terminate()

task.download_outputs()

task.print_summary()

To adapt it for this or any other use case, simply replace input_dir with the path to your OpenSees files and specify the sim_config_filename before running it in a Python script.

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

inductiva tasks info gafdcf5t0zpkft4sxmubo30q1

Task status: Success

Timeline:
	Waiting for Input         at 25/02, 16:35:31      1.995 s
	In Queue                  at 25/02, 16:35:33      20.562 s
	Preparing to Compute      at 25/02, 16:35:54      3.996 s
	In Progress               at 25/02, 16:35:58      28.221 s
		└> 28.09 s         /opt/openmpi/4.1.6/bin/mpirun --use-hwthread-cpus --np 4 OpenSeesMP Example.tcl
	Finalizing                at 25/02, 16:36:26      1.339 s
	Success                   at 25/02, 16:36:27      

Data:
	Size of zipped output:    23.23 MB
	Size of unzipped output:  59.07 MB
	Number of output files:   186

Estimated computation cost (US$): 0.00066 US$

Go to https://console.inductiva.ai/tasks/gafdcf5t0zpkft4sxmubo30q1 for more details.

The core computation time of our simulation was 28.2 seconds, as can be seen in the line In Progress at 25/02, 16:35:58 28.221 s. This part of the timeline represents the actual execution of the simulation.

Although it’s short, there’s still room for improvement to reduce the processing time.

Scaling Up Your Simulation#

Scaling up your simulation is as simple as changing just two lines of code:

1. Update the machine_type to a 16 vCPU machine (c2-standard-16)

2. Set the number of n_vcpus to 16

By increasing the number of vCPUs, we’ve reduced the processing time from 28.2 to 10.2 seconds.

Here are the results of running the same simulation on a few machines:

Still in the testing phase? No problem! Just skip this step for now and start with a machine with fewer vCPUs. Once you’re satisfied with your results, you can seamlessly scale your OpenSees simulation.