General Environment Setup to Work with SCU Resources

Setup Slurm

In order to use SCU resources, you'll first need to setup your environment to work properly with our implementation of the job scheduler, Slurm. This is described here: Using Slurm

Setup Spack

Once this is done, you'll need to setup your environment to use Spack, our cluster-wide package manager. This is described here: Spack


Relion-specific Environment Setup

In order to use the Relion graphical user interface (GUI), you'll need to do log on to curie, the Slurm submission node (see Using Slurm for more details), and add this to your ~/.bashrc:

export RELION_QSUB_EXTRA_COUNT=2
export RELION_QSUB_EXTRA1="Number of nodes:"
export RELION_QSUB_EXTRA1_DEFAULT="1"
export RELION_QSUB_EXTRA2="Number of GPUs:"
export RELION_QSUB_EXTRA2_DEFAULT="0"


After editing your ~/.bashrc, log out of curie.


Launching the Relion GUI

Log on to curie, with X11, and request an interactive node

ssh -Y pascal # if off campus, use ssh -Y pascal.med.cornell.edu
ssh -Y curie

The -Y enables the use of the GUI.


To request an interactive session, use this command (for more information, see: Using Slurm)

srun -n1 --pty --x11 --partition=cryo-cpu --mem=8G bash -l

Relion versions available

To see what's available, use this command (for more information on spack command, see Spack):

spack find -l -v relion


Here is output from the above command that is current as of 5/3/19:

==> 14 installed packages.
-- linux-centos7-x86_64 / gcc@4.8.5 -----------------------------
pbsqju2 relion@2.0.3 build_type=RelWithDebInfo ~cuda cuda_arch= +double~double-gpu+gui purpose=cluster
ua3zs52 relion@2.0.3 build_type=RelWithDebInfo +cuda cuda_arch=60 +double~double-gpu+gui purpose=cluster
djy46i6 relion@2.1 build_type=RelWithDebInfo +cluster+cuda cuda_arch=60 ~desktop+double~double-gpu+gui
cchnbyc relion@2.1 build_type=RelWithDebInfo ~cuda cuda_arch= +double~double-gpu+gui
xxisr7j relion@2.1 build_type=RelWithDebInfo +cuda cuda_arch=60 +desktop+double~double-gpu+gui
lzd4ktq relion@2.1 build_type=RelWithDebInfo +cuda cuda_arch=60 +double~double-gpu+gui
v6jckz3 relion@2.1 build_type=RelWithDebInfo +cuda cuda_arch=60 +double~double-gpu+gui purpose=cluster
6cpdlsc relion@2.1 build_type=RelWithDebInfo +cuda cuda_arch=60 +double~double-gpu+gui purpose=desktop
ltaf3x6 relion@2.1 build_type=RelWithDebInfo +cuda cuda_arch=70 +double~double-gpu+gui purpose=cluster
u6dzm4v relion@3.0_beta build_type=RelWithDebInfo ~cuda cuda_arch= +double~double-gpu+gui purpose=cluster
olcttts relion@3.0_beta build_type=RelWithDebInfo +cuda cuda_arch=60 +double~double-gpu+gui purpose=cluster
f2fjevh relion@3.0_beta build_type=RelWithDebInfo +cuda cuda_arch=60 +double~double-gpu+gui purpose=desktop
opdhbcs relion@3.0_beta build_type=RelWithDebInfo +cuda cuda_arch=70 +double~double-gpu+gui purpose=cluster
2ilkf4r relion@develop build_type=RelWithDebInfo +cuda+double~double-gpu+gui


There's a lot in the above output, so let's break it down!

First, in the above, we have several production-ready Relion versions:


In addition, these versions of Relion can run on the following platforms:


Some of these Relion installations are intended for use on nodes/workstations with GPUs, whereas others are intended for CPU-only nodes/workstations:

Do NOT try to run a +cuda installation of Relion on a CPU-only node–this will result in errors, as these versions of Relion expect CUDA to be present (which it is not on the CPU-only nodes).


Finally, we have versions of Relion that are specific to different GPU models:


What Relion version should I use?!?

Which version of Relion you use (2.0.3, 2.1, or 3.0_beta) is more of a scientific question than technical one; however, in general, most users seem to be using 3.0_beta, unless they have legacy projects that were started with an older version. 




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