NCMM CryoEM Computing platform

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The Luecke Group CryoEM setup data processing platform consists of three main servers:

  • intaristotle.intenal.biotek GPU server: 64 Intel Broadwell cores, 128 Gbytes of RAM, 4 x NVIDIA GTX 1080 GPU cards, 6 Tb of SSD scratch space
  • file server: 28 Intel Broadwell cores, 32 Gigs of RAM, 212 Tb of local disk space used as file server for the storage of CryoEM data. The machine is also used as a gateway to internal GPU/CPU processing nodes.

All nodes have 10 Gigabit Ethernet connectivity for dedicated NAS/NFS disk space between the file server and the current (and future) GPU compute nodes.


Aristotle/CryoMP Installation Documentation ( intaristotle.internal.biotek/ )

RT ticket #3135527

Live computational resource usage information (cpu and memory)

Software Installed, List of

Application Version on intaristotle.internal.biotek server Status Comments
ccp4 4.7.0 Done -
chimera 1.13.1 Done -
ctffind4 4.1.10 Done -
eman2 2.2 Done -
openssl 1.0.2o Done -
frealign 9.11 Done -
gautomatch 0.53 Done -
gctf 1.18 Done -
modules 4.20 Done -
mpich 3.0.4 Done -
motioncor2 1.2.1 Done -
nvidia cuda 8.0-GA1, 8.0-GA2, 9.0, 9.1, 9.2 Done -
openmpi 3.1.2 Done -
phenix 1.14-3260 Done -
relion 2.1, 3.0b Done -
sphire 1.1 Done -
xchimera 0.8 Done -

Top Directory ( /lsc )

Top directory for all installed software is /lsc

Source Files ( in case you need to re-compile something )

Source for all installed programs can be found under /lsc/sources

Dependencies for interactive 3D applications

VirtualGL: Running accelerated 3D graphics remotely via OpenGL

Located under /opt/VirtualGL
Loaded by default

VirtualGL is an open source toolkit that gives any Unix or Linux remote display software the ability to run OpenGL applications with full 3D hardware acceleration.

It is used to display 3D applications on a laptop that does not have a powerful 3D graphics card: Instead of letting the laptop render the 3D application, VirtualGL uses the (more powerful) graphics cards of the server to pre-render the application and send back the result.

This app is very useful in 3D applications like XChimera/Chimera, PyMol and the like

In order to take full advantage of this application, you need to be connected to the NCMM internal network, and not UiO.

Open the command-line/terminal of your choice and type

vglconnect intaristotle.internal.biotek

vgl connect will connect you to the internal interface for aristotle and set up the environment for executing a graphical application.

Let’s say we need to run chimera. So, we load the module

module load chimera/1.13.1

and then we use vglrun to run the chimera application

vglrun -d $DISPLAY chimera

The “-d $DISPLAY” argument is there just in case something has corrupted your local environment.

How was each piece of software compiled (flags, switches)


cd /lsc/sources/ccp4/4.7.0
mkdir -p /lsc/ccp4/4.7.0
cp -r /lsc/sources/ccp4/4.7.0/* /lsc/ccp4/4.7.0
cd /lsc/ccp4/4.7.0
# mucho bullshito, but yeah, welcome to scientific applications


cd /lsc/sources/chimera/1.13.1
./chimera-1.13.1-linux_x86_64.bin #self-extracts into two files
# answer questions
> Enter install location: /lsc/chimera/1.13.1
> Install desktop menu (icon has to be done by user)? no 
> Install symbolic link to chimera executable for command line use in which directory? [hit Enter for default (0)]: 0
# installer copies files into destination
> Installation is done; press return.


cd /lsc/sources/ctffind/4.1.10/ctffind-4.1.10
./configure --prefix=/lsc/ctffind4/4.1.10 --enable-latest-instruction-set
make -j 64 all
make -j 64 install


cd /lsc/sources/eman2/2.2/
> EMAN2 will now be installed into this location:
> [/root/EMAN2] >>> /lsc/eman2/2.2
# installer does the rest of the work, re-installing a bunch of python modules
#   via anaconda, cuz apparently the built-in package managers are less elitist
# *sigh* scientific computation, alright
> Do you wish the installer to prepend the EMAN2 install location
> to PATH in your /root/.bashrc ? [yes|no]
> [no] >>> no
> You may wish to edit your .bashrc to prepend the EMAN2 install location to PATH:
> export PATH=/opt/eman/2.2/bin:$PATH
# covered in the relevant environment module


cd /lsc/sources/openssl/openssl-1.0.2o/
./config --prefix=/lsc/external/openssl/1.0.2o
make -j 64
make -j 64 install


cd /lsc/sources/frealign/9.11/frealign_v9.11
mkdir -p /lsc/frealign/9.11
cp -r /lsc/sources/frealign/9.11/frealign_v9.11/* /lsc/frealign/9.11
# Ignore the ./INSTALL file, it does nothing
# you just need to add the relevant bin path for the application to work
# the relevant module covers the details


cd /lsc/sources/gautomatch/Gautomatch_v0.53
mkdir /lsc/gautomatch/0.53
cp -r /lsc/sources/gautomatch/Gautomatch_v0.53 /lsc/gautomatch/0.53


cd /lsc/sources/gctf/1.18
mkdir /lsc/gctf/1.18
cp -r /lsc/sources/gctf/1.18/* /lsc/gctf/1.18
# environmental module takes care of loading up cuda 8.0, (required) adding the bin path, and changing the LD_PRELOAD path ### modules 
cd /lsc/sources/modules/4.2.0
./configure --prefix=/lsc/modules --enable-doc-install --enable-example-modulefiles --enable-compat-version --enable-versioning --enable-quarantine-support --enable-auto-handling 
# since --enable-versioning is turned on, the module will autoversion itself and place all its files under
# /lsc/modules/4.2.0


default loaded by CentOS 7.
Environmental module was altered to make sure that it conflicts with the openmpi modules


cd /lsc/sources/motioncor2/1.2.1
mkdir -p /lsc/motioncor2/1.2.1/bin
cp -r /lsc/sources/motioncor2/1.2.1/* /lsc/motioncor2/1.2.1a
ln -s /lsc/motioncor2/1.2.1/MotionCor2_1.2.1-Cuda80 /lsc/motioncor2/1.2.1/bin/motioncor2
# environmental module takes care of setting up the bin path 


cd /lsc/sources/nvidia/drivers/396.54;

Update: In order to combat the issue with creating remote OpenGL context (X11 forwarding over ssh), I upgraded the driver to 415.23 but had no luck. In nvidia-smi, the new driver reports that is nvidia CUDA 10 capable, which is fine as it can use the CUDA 8 run-time environment, as NVIDIA guarantees binary compatibility


CUDA frameworks installed:

  • 8.0-GA1
  • 8.0-GA2
  • 9.0
  • 9.1
  • 9.2
Default CUDA framework for all applications is 8.0GA1

NVidia Driver installed is 396.54, short-term support as of 2018-10-31, as per above.

Default driver installed with CUDA 8.0-GA1 is 375.64 (not installed, obviously)

During loading different CUDA versions, NVIDIA driver remains the same. Things seem to work, but may require future additional detailed testing

All CUDA installations require gcc 4.8 (hence the reason we went with CentOS)

All mentioned versions are currently installed, but we regard 8.0-GA1 as the base release, due to software that demands 8.0-GA1 and has no alternatives.



cd /lsc/sources/nvidia/cuda/8.0-GA1 ;
./cuda_8.0.44_linux-run --silent --toolkit=/lsc/nvidia/cuda/8.0-GA1 --samples --samplespath=/lsc/nvidia/cuda/8.0-GA1/samples --run-nvidia-xconfig --tmpdir=/tmp


cd /lsc/sources/nvidia/cuda/8.0-GA2 ;
./cuda_8.0.61_375.26_linux-run --silent --toolkit=/lsc/nvidia/cuda/8.0-GA2 --samples --samplespath=/lsc/nvidia/cuda/8.0-GA2/samples --run-nvidia-xconfig --tmpdir=/tmp


cd /lsc/sources/nvidia/cuda/9.0 ;
./cuda_9.0.176_384.81_linux-run --silent --toolkit=/lsc/nvidia/cuda/9.0 --samples --samplespath=/lsc/nvidia/cuda/9.0/samples --run-nvidia-xconfig --tmpdir=/tmp


cd /lsc/sources/nvidia/cuda/9.1 ;
./cuda_9.1.85_387.26_linux --silent --toolkit=/lsc/nvidia/cuda/9.1 --samples --samplespath=/lsc/nvidia/cuda/9.1/samples --run-nvidia-xconfig --tmpdir=/tmp


cd /lsc/sources/nvidia/cuda/9.2 ;
./9.2.148_396.37_linux --silent --toolkit=/lsc/nvidia/cuda/9.2 --samples --samplespath=/lsc/nvidia/cuda/9.2/samples --run-nvidia-xconfig --tmpdir=/tmp


cd /lsc/sources/openmpi/3.1.2;
./configure --prefix /lsc/openmpi/3.1.2 --enable-binaries --enable-mpi-fortran --with-cuda=/lsc/nvidia/cuda/8.0-GA1 --with-devel-headers 

Default: 3.1.2

The default version loaded is the stable-as-of 2018-10-31 3.1.2


cd /lsc/sources/phenix/1.14/phenix-installer-1.14-3260-intel-linux-2.6-x86_64-centos6 ;
./install --prefix=/lsc/phenix/1.14-3260 --openmp --makedirs 



cd /lsc/sources/relion/2.1-mpich ;
mkdir build;
cmake -DCMAKE_INSTALL_PREFIX=/lsc/relion/2.1
make -j 64
make -j 64 install


cd /lsc/sources/relion/3.0b-mpich ;
mkdir build;
cmake -DCMAKE_INSTALL_PREFIX=/lsc/relion/3.0b
make -j 64
make -j 64 install


cd /lsc/sources/sphire/1.1 ;
# follow questions, install under /lsc/sphire/1.1

How is each piece of software run ( really basic, just front UI, text or graphics)



module load chimera


module load ctffind4


module load eman



Nothing to see here, this is just a support library


module load frealign


module load gautomatch


module load gctf


module load mpich




modinfo nvidia

cuda/{ 8.0-GA1, 8.0-GA2, 9.0, 9.1, 9.2 }

There is really nothing you can do with the CUDA libraries directly

You can only verify that version of CUDA works with the following for loop in bash:

for version in 8.0-GA1 8.0-GA2 9.0 9.1 9.2; 
    module switch nvidia/cuda/$version; # press q to quit the nbody simulation below
    /lsc/nvidia/cuda/$version/samples/5_Simulations/nbody/nbody -hostmem -numdevices=$(lspci | grep -i nvidia | grep -i vga); # n-body gravitational attraction simulation
done && module purge;


module load openmpi
mpirun -j 64 date


module load phenix

relion/{ 2.1, 3.0b }

for version in 2.1 3.0b; 
    module switch relion/$version;


module load sphire


not yet available   

Environmental Modules

To see what environment modules are available:

module avail

To load a module:

module load <module>

To see the already loaded modules:

module list

To unload a module:

module unload <module>

Git Repo

Pushing them to the nodes via Ansible + git

Running Test Jobs on Aristotle to test the software


As per the Relion 3.0 tutorial:

You will need the following test sets:

These test sets are already downloaded and untar'ed under intaristotle.internal.biotek:/lsc/relion/test_data

module load relion/$version you need and wait for relion to open on your X server.

3D Classification

Follow the instructions in the tutorial regarding 3D classification