FAQ

How do I convert my Python Multiprocessing program to Dragon ?

How do I debug my Dragon program ?

Use the -l option when running Dragon, e.g., dragon -l DEBUG my_app.py. Possible log levels are NONE, DEBUG, INFO, WARNING, ERROR, or CRITICAL. The Dragon logs will show debug output from all services alongside your program.

How can I change the size of the default memory pool ?

The size of the default memory pool in bytes is controlled by the environment variable DEFAULT_SEG_SZ during startup. The default is 2^32 or four GBytes per node. If we want to increase the memory to eight GBytes, we set the variable as follows in bash: export DRAGON_DEFAULT_SEG_SZ=8589934592.

How do I find the p_uid of the current process ?

Python Multiprocessing: multiprocessing.current_process().pid. Note that Dragon replaces the OS pid with the p_uid, as the pid is not unique on a Distributed System.
Dragon Native: dragon.native.process.current()
Dragon Client & Infrastructure: dragon.infrastructure.parameters.this_process.my_puid

How do I enable the (TCP|RDMA)-based transport ?

References to a RDMA-based transport exist in a few places in the documentation and refer to an optional extension which is not included in the open-source version of Dragon. For inquiries about Dragon’s high speed RDMA-based transport, please contact HPE by emailing dragonhpc@hpe.com.

The TCP-based transport is enabled by default. To specify use of the RDMA (where available) or TCP-based transport explicitly, the Dragon launcher provides the --transport option, though the only choice on the open source implementation is tcp.

# Explicitly use the RDMA-based transport
$ dragon --transport hsta my-dragon-script.py

# Use the tcp-based transport via the runtime's default setting
$ dragon my-dragon-script.py

# Use the TCP-based transport
$ dragon --transport tcp my-dragon-script.py

Where can I find the Environment Variables that control the Dragon Run-time ?

See Environment Variables.

What do I do if I need to clean up any Dragon processes or experiments that did not complete properly?

In the event your experiment goes awry, we provide a helper script, dragon-cleanup, to clean up any zombie processes and memory. The script dragon-cleanup is placed in the [dragon install dir]/bin and added to the $PATH environment variable after loading the Dragon module.

Can I use Dragon to manage MPI jobs?

This functionality is currently only available on systems where the HPE Cray MPITCH library is installed.

How can I get the best performance from my Distributed Dictionary?

There are a number of performance tips and tricks and in the enclosing section on the Design of the Distributed Dictionary, where many examples are also provided.