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Run Settings

Run Settings#

Overview#

RunSettings are used in the SmartSim API to define how Model and Ensemble jobs should be executed.

In general, RunSettings define:

  • the executable

  • the arguments to pass to the executable

  • necessary environment variables at runtime

  • the required compute resources

The base RunSettings class is utilized for local task launches, while its derived child classes offer specialized functionality for HPC workload managers (WLMs). Each SmartSim launcher interfaces with a specific RunSettings subclass tailored to an HPC job scheduler.

  • Navigate to the Local section to configure run settings locally

  • Navigate to the HPC Systems section to configure run settings for HPC

A RunSettings object is initialized through the Experiment.create_run_settings function. This function accepts a run_command argument: the command to run the executable.

If run_command is set to “auto”, SmartSim will attempt to match a run command on the system with a RunSettings class. If found, the class corresponding to that run_command will be created and returned.

If the run_command is passed a recognized run command (e.g. “srun”) the RunSettings instance will be a child class such as SrunSettings. You may also specify “mpirun”, “mpiexec”, “aprun”, “jsrun” or “orterun” to the run_command argument. This will return the associated child class.

If the run command is not supported by SmartSim, the base RunSettings class will be created and returned with the specified run_command and run_args evaluated literally.

After creating a RunSettings instance, users gain access to the attributes and methods of the associated child class, providing them with the ability to further configure the run settings for jobs.

Examples#

Local#

When running SmartSim on laptops and single node workstations via the “local” launcher, job execution is configured with the base RunSettings object. For local launches, RunSettings accepts a run_command parameter to allow the use of parallel launch binaries like “mpirun”, “mpiexec”, and others.

If no run_command is specified and the Experiment launcher is set to “local”, the executable is launched locally. When utilizing the “local” launcher and configuring the run_command parameter to “auto” in the Experiment.create_run_settings factory method, SmartSim defaults to omitting any run command prefix before the executable.

Once the RunSettings object is initialized using the Experiment.create_run_settings factory method, the RunSettings API can be used to further configure the RunSettings object prior to execution.

Note

The local launcher is the default launcher for all Experiment instances.

When the user initializes the Experiment at the beginning of the Python driver script, a launcher argument may be specified. SmartSim will register or detect the launcher and return the supported class upon a call to Experiment.create_run_settings. Below we demonstrate creating and configuring the base RunSettings object for local launches by specifying the “local” launcher during Experiment creation. We also demonstrate specifying run_command=”mpirun” locally.

Initialize and Configure a RunSettings Object with No Run Command Specified:

from smartsim import Experiment

# Initialize the experiment and provide launcher local
exp = Experiment("name-of-experiment", launcher="local")


# Initialize a RunSettings object
run_settings = exp.create_run_settings(exe="echo", exe_args="Hello World", run_command=None)

Initialize and Configure a RunSettings Object with the `mpirun` Run Command Specified:

Note

Please note that to run this example you need to have an MPI implementation (e.g. OpenMPI or MPICH) installed.

from smartsim import Experiment

# Initialize the experiment and provide launcher local
exp = Experiment("name-of-experiment", launcher="local")

# Initialize a RunSettings object
run_settings = exp.create_run_settings(exe="echo", exe_args="Hello World", run_command="mpirun")

Users may replace mpirun with mpiexec.

HPC System#

To configure an entity for launch on an HPC system, SmartSim offers RunSettings child classes. Each WLM launcher supports different RunSettings child classes. When the user initializes the Experiment at the beginning of the Python driver script, a launcher argument may be specified. The specified launcher will be used by SmartSim to return the correct RunSettings child class that matches with the specified (or auto-detected) run_command upon a call to Experiment.create_run_settings. Below we demonstrate creating and configuring the base RunSettings object for HPC launches by specifying the launcher during Experiment creation. We show examples for each job scheduler.

The Slurm launcher supports the SrunSettings API as well as the MpirunSettings API, MpiexecSettings API and OrterunSettings API that each can be used to run executables with launch binaries like “srun”, “mpirun”, “mpiexec” and “orterun”. Below we step through initializing a SrunSettings and MpirunSettings instance on a Slurm based machine using the associated run_command.

SrunSettings

Run a job with the srun command on a Slurm based system. Any arguments passed in the run_args dict will be converted into srun arguments and prefixed with “–”. Values of None can be provided for arguments that do not have values.

from smartsim import Experiment

# Initialize the Experiment and provide launcher Slurm
exp = Experiment("name-of-experiment", launcher="slurm")

# Initialize a SrunSettings object
run_settings = exp.create_run_settings(exe="echo", exe_args="Hello World", run_command="srun")
# Set the number of nodes
run_settings.set_nodes(4)
# Set the number of cpus to use per task
run_settings.set_cpus_per_task(2)
# Set the number of tasks for this job
run_settings.set_tasks(100)
# Set the number of tasks for this job
run_settings.set_tasks_per_node(25)

MpirunSettings

Run a job with the mpirun command (MPI-standard) on a Slurm based system. Any arguments passed in the run_args dict will be converted into mpirun arguments and prefixed with “–”. Values of None can be provided for arguments that do not have values.

from smartsim import Experiment

# Initialize the Experiment and provide launcher Slurm
exp = Experiment("name-of-experiment", launcher="slurm")

# Initialize a MpirunSettings object
run_settings = exp.create_run_settings(exe="echo", exe_args="Hello World", run_command="mpirun")
# Set the number of cpus to use per task
run_settings.set_cpus_per_task(2)
# Set the number of tasks for this job
run_settings.set_tasks(100)
# Set the number of tasks for this job
run_settings.set_tasks_per_node(25)

Users may replace mpirun with mpiexec or orterun.

Note

SmartSim will look for an allocation by accessing the associated WLM job ID environment variable. If an allocation is present, the entity will be launched on the reserved compute resources. A user may also specify the allocation ID when initializing a run settings object via the alloc argument. If an allocation is specified, the entity receiving these run parameters will launch on that allocation.

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