To cite pyiron and the corresponding codes, please follow the instructions on the publication page.
pyiron is designed to be installed as centralized service on your local computer cluster, rather than a local installation on each individual workstation. To test pyiron online or with a local installation, please follow the instructions on the installation page.
The linking of executables is explained as part of the installation here. By default pyiron links to the executables provided by conda but you can accelerate you calculation by compiling your own version of a given simulation code which is optimized for your hardware.
While most examples execute calculations inline or in modal mode, it is also possible to send calculation in the background.
job.server.run_mode.non_modal = True
job.run()
print("execute other commands while the job is running.")
pr.wait_for_job(job)In this example the job is executed in the background, while the print command is already executed. Afterwards the project object waits for the execution of the job in the background to be finished.
Just like executing calculation in the background it is also possible to submit calculation to the queuing system:
job.server.list_queues() # returns a list of queues available on the system
job.server.view_queues() # returns a DataFrame listing queues and their settings
job.server.queue = "my_queue" # select a queue
job.server.cores = 80 # set the number of cores
job.server.run_time = 3600 # set the run time in seconds
job.run()For the queuing system to be available in pyiron it is necessary to configure it. The configuration of different queuing systems is explained in the installation.
pyiron is the combination of py + iron connecting Python, the programming language with iron as pyiron was initially developed at the Max Planck Institut für Eisenforschung (iron research).
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