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BigJob Tutorial Part 6: Coupled Ensemble Example
This page is part of the BigJob Tutorial.
The script provides a simple workflow which submit a set of jobs(A) and jobs(B) and wait until they are completed and then submits set of jobs(C). It demonstrates synchronization mechanisms provided by SAGA Pilot-API.
What types of workflows would this be useful for?
If the executable in C has dependencies on some of the output generated from jobs A and B.
In your $HOME directory, open a new file coupled_ensemble.py with your favorite editor (e.g., vim) and paste the following content:
import os
import time
import sys
from pilot import PilotComputeService, ComputeDataService, State
### This is the number of jobs you want to run
NUMBER_JOBS=4
COORDINATION_URL = "redis://[email protected]:6379"
if __name__ == "__main__":
pilot_compute_service = PilotComputeService(COORDINATION_URL)
pilot_compute_description = { "service_url": "sge://localhost",
"number_of_processes": 12,
"allocation": "XSEDE12-SAGA",
"queue": "development",
"working_directory": os.getenv("HOME")+"/agent",
"walltime":10
}
pilot_compute_service.create_pilot(pilot_compute_description=pilot_compute_description)
compute_data_service = ComputeDataService()
compute_data_service.add_pilot_compute_service(pilot_compute_service)
print ("Finished Pilot-Job setup. Submitting compute units")
# submit a set of CUs, call it A
for i in range(NUMBER_JOBS):
compute_unit_description = { "executable": "/bin/echo",
"arguments": ["Hello","$ENV1","$ENV2"],
"environment": ['ENV1=env_arg1','ENV2=env_arg2'],
"number_of_processes": 1,
"output": "A_stdout.txt",
"error": "A_stderr.txt"
}
compute_data_service.submit_compute_unit(compute_unit_description)
# submit a set of CUs, call it B
for i in range(NUMBER_JOBS):
compute_unit_description = { "executable": "/bin/date",
"arguments": [],
"environment": {},
"number_of_processes": 1,
"output": "B_stdout.txt",
"error": "B_stderr.txt",
}
compute_data_service.submit_compute_unit(compute_unit_description)
print ("Wait for CUs of task set A & B to complete")
compute_data_service.wait()
# submit a set of CUs, call it C
for i in range(NUMBER_JOBS):
compute_unit_description = { "executable": "/bin/echo",
"arguments": ["Hello","$ENV1","$ENV2"],
"environment": ['ENV1=env_arg1','ENV2=env_arg2'],
"number_of_processes": 1,
"spmd_variation":"single",
"output": "C_stdout.txt",
"error": "C_stderr.txt",
}
compute_data_service.submit_compute_unit(compute_unit_description)
print ("Wait for CUs of task set C to complete")
compute_data_service.wait()
print ("Terminate Pilot Jobs")
compute_data_service.cancel()
pilot_compute_service.cancel()
Execute the script using command
python coupled_ensemble.py
Can you identify whether jobs of set (C) executed after jobs of set A & B?
You will have to go into the working directory (which is $HOME/agent in this case), then the directory named after the pilot-service (i.e. bj-####), and then the compute unit directories associated with that pilot-service (i.e. sj-###). Note that bj-#### is the unique identifier of each Pilot-Job. sj-### is the unique identifier associated with each subjob. When creating your own jobs, you can change the name of the subjob directories to have more human-readable names.
Check the time stamps of the compute unit output file (sj-stdout.txt).