Target Machines for Executing AL Workflows¶

ROSE enables the execution of AL workflows on diverse computing resources. Below, we will show how you can specify your local computer and remote HPC machine as target resources.

Local Computer¶

For local execution, user can use their desktops, laptops, and their own small clusters to execute their AL workflows as follows:

import os

from rose.engine import ResourceEngine
from rose.learner import ActiveLearner

engine = ResourceEngine({'runtime': 30,
                         'resource': 'local.localhost'})
acl = ActiveLearner(engine)

HPC Resources¶

To execute AL workflows on HPC machines, users must have an active allocation on the target machine and specify their resource requirements, as well as the time needed to execute their workflows. Remember, ROSE is based on RADICAL-Pilot. For more information on how to access, set up, and execute workflows on HPC machines, refer to the following link RADICAL-Pilot Job Submission:

import os

from rose.engine import ResourceEngine
from rose.learner import ActiveLearner


hpc_engine = ResourceEngine({'runtime': 30,
                             'cores': 4096,
                             'gpus' : 4,
                             'resource': 'tacc.frontera'})
acl = ActiveLearner(engine)