![]() ![]() CondaĬonda is a tool commonly used to install Python software along with dependencies and manage virtual environments on a laptop or workstation. To use the virtual environment in a cluster job script, simply activate it there the same way. Next, load the appropriate supporting modules: In this case, mpi4py requires a working MPI so you must choose the one that most fits your needs (hint: You can invoke the " module avail" command to see which MPI are available).Ģ. Using mpi4py as an example, the steps to do this are as follows:ġ. First, figure out if there are any prerequisites that need to be met. Install the module into the $HOME/.local directory. A few popular methods for doing this are described below. If the module that you want is not available, then you may install it into your home directory. Alternatively, look at the stack contents on the Wiki, Argon Software List - Python To do so, simply load the desired Python environment, enter the Python help system, and list the installed modules. If there is a Python module that you are interested in using, you can see if it is available in one of our offered Python environments. We have attempted to add the most commonly-known scientific and data analysis modules that are available into the centrally available Python environments. So, if your code performs best with 4 threads and using MKL, set ![]() Be sure to request an appropriate number of jobs slots from SGE when adjusting that. If your code will perform better with threads then set that variable to the optimal number. To avoid inadvertently overloading compute nodes this is set to 1. This is controlled with the OMP_NUM_THREADS environment variable. If using a Python linked against MKL then you have the option of using OpenMP threads. Otherwise you will get the system python installation, which is part of the system but lacks many features because it's not maintained as a piece of research software. Generally, we provide stacks built with the Intel compiler and MKL.Īlso, note that you should generally load a python environment module before using python in a job script. ![]() Note that the stacks are not equal in terms of extensions installed, although stacks of the same python version should have the same extensions. ![]()
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