Troubleshooting Simulations

This guide covers tips and strategies for troubleshooting simulation failures.

Log Debug information

Note

When using a scheduler (e.g. SLURM), be sure to specify output files for standard out and standard error. For example, when using SLURM both --output= and --error= must be set to view errors.

One of the first troubleshooting steps is to increase the verbosity of the logging. openfe uses Python’s native logging library which can be configured either using a Python API or a configuration file.

Warning

We do not recommend setting the log level to debug for production runs, as the logging may slow down the simulation and add a lot of noise to the output.

When using openfe quickrun, the configuration file is more convenient. Below is an example logging configuration file that can be used to set the log level to DEBUG:

[loggers]
keys=root

[handlers]
keys=stdout

[formatters]
keys=standardFormatter,msgOnly

[handler_stdout]
class=StreamHandler
level=DEBUG
formatter=standardFormatter
args=(sys.stdout,)

[logger_root]
level=DEBUG
handlers=stdout

[formatter_standardFormatter]
format=%(asctime)s %(levelname)s %(name)s: %(message)s

[formatter_msgOnly]
format=%(message)s

Save this configuration file as debug_logging.conf and then run openfe quickrun with the --log flag, for example:

$ openfe --log debug_logging.conf quickrun -d results/ -o results/result_lig_ejm_31_solvent_lig_ejm_42_solvent.json transformations/rbfe_lig_ejm_31_solvent_lig_ejm_42_solvent.json

Note that the --log debug_logging.conf argument goes between openfe and quickrun on the command line.

This will cause every package to log at the debug level, which may be quite verbose and noisy but should aid in identify what is going on right before the exception is thrown.

JAX warnings

We use pymbar to analyze the free energy of the system. pymbar uses JAX to accelerate computation. The JAX library can utilize a GPU to further accelerate computation. If the necessary libraries for GPU acceleration are not installed and JAX detects a GPU, JAX will print a warning like this:

WARNING:2025-06-10 09:01:40,857:jax._src.xla_bridge:966: An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.

This warning does not mean that the molecular dynamics simulation will fall back to using the CPU. The simulation will still use the computing platform specified in the settings.