4.1. Simple Bag-of-Tasks

The simplest usage of a pilot system is to collectively submit and execute multiple identical tasks (a ‘Bag of Tasks’ or ‘BoT’) either locally or on a remote high-performance computing (HPC) machine. In this way, a pilot system allows to code and execute parameter sweep or ensemble simulation applications.

We create an example which submits N tasks using RADICAL-Pilot. All tasks are identical, except that each task outputs its unique ID. RADICAL-Pilot (1) submits one container job called pilot to the queuing system of the HPC machine and, when this pilot becomes active, (2) it schedules and execute the N tasks on the resources of that pilot. In this way, each task is not individually submitted as a job to the queuing system of the HPC machine.

4.1.1. Preparation

Download the file simple_bot.py with the following command:

curl -O https://raw.githubusercontent.com/radical-cybertools/radical.pilot/master/examples/docs/simple_bot.py

Open the file simple_bot.py with your favorite editor. The example should work right out of the box on your local machine. However, if you want to run it on a remote HPC machine, look for the sections marked:


and change the code below that line, according to the instructions in the comments.

4.1.2. Execution

This assumes you have installed RADICAL-Pilot in a Python virtualenv. You also need access to a MongoDB server.

Set the RADICAL_PILOT_DBURL environment variable in your shell to the MongoDB server you want to use, for example:

export RADICAL_PILOT_DBURL=mongodb://<user>:<pass>@<host>:<port>/<database>

If RADICAL-Pilot is installed and the MongoDB URL is set, you should be good to run your program (the database is created on the fly):

python simple_bot.py

The output should look something like this:

Initializing Pilot Manager ...
Submitting Pilot to Pilot Manager ...
Initializing Task Manager ...
Registering Pilot with Task Manager ...
Submit Tasks to Task Manager ...
Waiting for CUs to complete ...
Waiting for CUs to complete ...
All CUs completed!
Closed session, exiting now ...

4.1.3. Logging and Debugging

Since working with distributed systems is inherently complex and much of the complexity is hidden within RADICAL-Pilot, it is necessary to do internal logging. By default, logging output is disabled, but if something goes wrong or if you’re just curious, you can enable the logging output by setting the environment variable RADICAL_PILOT_LOG_LVL to a value between CRITICAL (print only critical messages) and DEBUG (print all messages). For more details on logging, see under ‘Debugging’ in chapter Developer Documentation.

Give it a try with the above example:

RADICAL_PILOT_LOG_LVL=DEBUG python simple_bot.py