![]() ![]() ![]() Python or Conda virtual environment base: specify the top-level directory of a custom virtual env, or the base directory of a conda environment.Modules: a space-separated list of modules to be loaded.If these are under /g/data or /scratch make sure you've included the appropriate directive(s) in your storage options above. Module directories: a space-separated list of additional directories to search for modulefile definitions.Optionally use the advanced options to specify an alternative JupyterLab installation or other module files that your notebooks use.This is useful when the cluster is busy and your session is queued waiting for a free slot if you want to receive an email once your session has started.select additional software licenses if required for your job.select what storage (gdata and scratch areas) are required for your job to run. ![]() select which project to allocate the SU from (must be a project with a current allocation, or the session will not start).using Dask) then you may not need a very large JupyterLab session Note: this is the resources used within the notebook if you offload the processing to other jobs (e.g. If you exceed the memory your Jupyter Kernel may be terminated. If you attempt to exceed the CPU limit your processes will be throttled to the amount requested. the size of the compute resources you have access to (maximum).the compute queue you want to submit the job to.the number of hours you want your session to run for (maximum).Click the JupyterLab icon on the Dashboard (home page). ![]()
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