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I have written a python code, named MPjobs, that allow running as many instances of PSSe as CPU’s in a pc, in other words, runs PSSe in parallel at the process level. It uses pool.apply_async and a dictionary to pass the arguments. This tool is suitable for repetitive studies where the changing variable is known, like during benchmarking models, sensitivity runs or dynamic fault simulations.

You can download the MPjobs code with a PSSe v.33 demo set from [copy the link into your browser if it does not work by clicking on it]:

At JContogoogledrive, enter the folder "MPjobs PSSe in Parallel" and then select “MPjobsjconto_xxxxx.zip”. An icon on the top-center screen will perform the download.

As it is, MPjobs can be used to parallelize runs from ‘almost’ any application that can run from a DOS window with an input file or line arguments.

Follow the instruction in the read.me file and in the wiki doc to run the demos included.

I have written a python code, named MPjobs, that allow running as many instances of PSSe as CPU’s in a pc, in other words, runs PSSe in parallel at the process level. It uses pool.apply_async and a dictionary to pass the arguments. This tool is suitable for repetitive studies where the changing variable is known, like during benchmarking models, sensitivity runs or dynamic fault simulations.

[Updated 20201103] You can download the MPjobs code with a PSSe v.33 v.33/v.34 (and python 2.7 or v.3.7) demo set sets from [copy the link into your browser if it does not work by clicking on it]:

At JContogoogledrive, enter the folder "MPjobs PSSe in Parallel" and then select “MPjobsjconto_xxxxx.zip”. An icon on the top-center screen will perform the download.

As it is, MPjobs can be used to parallelize runs from ‘almost’ any application that can run from a DOS window with an input file or line arguments.

Follow the instruction in the read.me file and in the wiki doc to run the demos included.

I have written a python code, named MPjobs, that allow running as many instances of PSSe as CPU’s in a pc, in other words, runs PSSe in parallel at the process level. It uses pool.apply_async and a dictionary to pass the arguments. This tool is suitable for repetitive studies where the changing variable is known, like during benchmarking models, sensitivity runs or dynamic fault simulations.

[Updated 20201103] 20210629] You can download the MPjobs code tool with a PSSe v.33/v.34 demo set compatible with PSSe v.33, v.34 and v.35 (and python 2.7 or v.3.7) demo sets 2.7, v.3.7, v.3.8) from [copy the link into your browser if it does not work by clicking on it]:

At JContogoogledrive, enter the folder "MPjobs PSSe in Parallel" and then select “MPjobsjconto_xxxxx.zip”. An icon on the top-center screen will perform the download.

As it is, MPjobs can be used to parallelize runs from ‘almost’ any application that can run from a DOS window with an input file or line arguments.

Follow the instruction in the read.me file and in the wiki doc to run the demos included.