ACLAB
General Information
- ACLAB is a private virtual cluster in Red Cloud with restricted access to the following groups: ktb1_0005. Please see Virtual Cluster in Red Cloud page for more usage information.
- PIs are Adam Anderson and Eve DeRosa.
- Head node: aclab.cac.cornell.edu (access via ssh)
- OpenHPC deployment running Centos 8
- Cluster scheduler: slurm
- The Slurm Quick Start guide is a great place to start.
- compute nodes - on demand via slurm
- data on the ACLAB cluster storage is NOT backed up
- Please send any questions and report problems to: cac-help@cornell.edu?subject=ACLAB
Remote File Access
From the Cornell campus network, users can access aclab file systems remotely from their computers:
- Home Directories: users can access home directories at smb://aclab.cac.cornell.edu (Linux or macOS) or \aclab.cac.cornell.edu (Windows)
- /home/shared/aclab-fmri: users can access this directory at smb://aclab.cac.cornell.edu/aclab-fmri (Linux or macOS) or \aclab.cac.cornell.edu\aclab-fmri (Windows)
You must specify the domain along with your user name
Prepend (or append) your domain to your CAC username as shown below.
Specify the domain in the username field
Make sure you prefix your CAC username with ctc_ith\
when entering your credentials. Replace <cac_user_name>
with your cac user name:
- username:
ctc_ith\<cac_user_name>
- password:
your_CAC_password
Alternatively, you can append @tc.cornell.edu
to your username:
- username:
<cac_user_name>@tc.cornell.edu
- password:
your_CAC_password
Software
Work with Environment Modules
Set up the working environment for each package using the module command. The module command will activate dependent modules if there are any. To show currently loaded modules: (These modules are loaded by default system configurations)
-bash-4.2$ module list
Currently Loaded Modules:
1) autotools 3) gnu9/9.3.0 5) libfabric/1.10.1 7) ohpc
2) prun/2.0 4) ucx/1.8.0 6) openmpi4/4.0.4
To show all available modules:
-bash-4.2$ module avail
-------------------- /opt/ohpc/pub/moduledeps/gnu9-openmpi4 --------------------
adios/1.13.1 netcdf-fortran/4.5.2 py3-mpi4py/3.0.3
boost/1.73.0 netcdf/4.7.3 py3-scipy/1.5.1
fftw/3.3.8 opencoarrays/2.8.0 scalapack/2.1.0
hypre/2.18.1 petsc/3.13.1 slepc/3.13.2
mfem/4.1 phdf5/1.10.6 superlu_dist/6.1.1
mumps/5.2.1 pnetcdf/1.12.1 trilinos/13.0.0
netcdf-cxx/4.3.1 ptscotch/6.0.6
------------------------ /opt/ohpc/pub/moduledeps/gnu9 -------------------------
gsl/2.6 mpich/3.3.2-ofi openmpi4/4.0.4 (L)
hdf5/1.10.6 mvapich2/2.3.2 py3-numpy/1.19.0
metis/5.1.0 openblas/0.3.7 superlu/5.2.1
-------------------------- /opt/ohpc/pub/modulefiles ---------------------------
autotools (L) libfabric/1.10.1 (L) pmix/3.1.4
cmake/3.16.2 ohpc (L) prun/2.0 (L)
gnu9/9.3.0 (L) os ucx/1.8.0 (L)
Where:
L: Module is loaded
Use "module spider" to find all possible modules and extensions.
Use "module keyword key1 key2 ..." to search for all possible modules matching any of the "keys".
To load a module and verify:
-bash-4.2$ module load cmake
-bash-4.2$ module list
Currently Loaded Modules:
1) autotools 3) gnu9/9.3.0 5) libfabric/1.10.1 7) ohpc
2) prun/2.0 4) ucx/1.8.0 6) openmpi4/4.0.4 8) cmake/3.16.2
Manage Modules in Your Python Virtual Environment
python 3.6.8 is installed. Users can manage their own python environment (including installing needed modules) using virtual environments. Please see the documentation on virtual environments on python.org for details.
Create Virtual Environment
You can create as many virtual environments, each in their own directory, as needed.
python3 -m venv <your virtual environment directory>
Activate Virtual Environment
You need to activate a virtual environment before using it:
source <your virtual environment directory>/bin/activate
Install Python Modules Using pip
After activating your virtual environment, you can now install python modules for the activated environment:
-
It's always a good idea to update
pip
first:pip install --upgrade pip
-
Install the module
pip install <module name>
-
List installed python modules in the environment:
pip list modules
-
Examples: Install
tensorflow
andkeras
like this:-bash-4.2$ python3 -m venv tensorflow -bash-4.2$ source tensorflow/bin/activate (tensorflow) -bash-4.2$ pip install --upgrade pip Collecting pip Using cached https://files.pythonhosted.org/packages/30/db/9e38760b32e3e7f40cce46dd5fb107b8c73840df38f0046d8e6514e675a1/pip-19.2.3-py2.py3-none-any.whl Installing collected packages: pip Found existing installation: pip 18.1 Uninstalling pip-18.1: Successfully uninstalled pip-18.1 Successfully installed pip-19.2.3 (tensorflow) -bash-4.2$ pip install tensorflow keras Collecting tensorflow Using cached https://files.pythonhosted.org/packages/de/f0/96fb2e0412ae9692dbf400e5b04432885f677ad6241c088ccc5fe7724d69/tensorflow-1.14.0-cp36-cp36m-manylinux1_x86_64.whl : : : Successfully installed absl-py-0.8.0 astor-0.8.0 gast-0.2.2 google-pasta-0.1.7 grpcio-1.23.0 h5py-2.9.0 keras-2.2.5 keras-applications-1.0.8 keras-preprocessing-1.1.0 markdown-3.1.1 numpy-1.17.1 protobuf-3.9.1 pyyaml-5.1.2 scipy-1.3.1 six-1.12.0 tensorboard-1.14.0 tensorflow-1.14.0 tensorflow-estimator-1.14.0 termcolor-1.1.0 werkzeug-0.15.5 wheel-0.33.6 wrapt-1.11.2 (tensorflow) -bash-4.2$ pip list modules Package Version -------------------- ------- absl-py 0.8.0 astor 0.8.0 gast 0.2.2 google-pasta 0.1.7 grpcio 1.23.0 h5py 2.9.0 Keras 2.2.5 Keras-Applications 1.0.8 Keras-Preprocessing 1.1.0 Markdown 3.1.1 numpy 1.17.1 pip 19.2.3 protobuf 3.9.1 PyYAML 5.1.2 scipy 1.3.1 setuptools 40.6.2 six 1.12.0 tensorboard 1.14.0 tensorflow 1.14.0 tensorflow-estimator 1.14.0 termcolor 1.1.0 Werkzeug 0.15.5 wheel 0.33.6 wrapt 1.11.2
Software List
Software | Path | Notes |
---|---|---|
*GNU Compilers 9.3.0 | /opt/ohpc/pub/compiler/gcc/9.3.0 | module load |
*openmpi 4.0.4 | /opt/ohpc/pub/mpi/openmpi4-gnu9 | module load openmpi4 |
AFNI | /opt/ohpc/pub/apps/afni | module load afni |
Freesurfer 7.2.0 | /opt/ohpc/pub/apps/freesurfer/7.2.0 | module load freesurfer/7.2.0 |
PyQt4 4.12.3 | /opt/ohpc/pub/libs/gnu9/PyQt4/4.12.3 | module load py3-PyQt4/4.12.3 |