Difference between revisions of "ALTAS Cluster"
(Created page with "This is a private cluster. =Hardware= :* Head node: '''hopper.cac.cornell.edu'''. :* Access modes: ssh :* OpenHPC 2.3 with Rocky Linux 8.4 :* 22 compute nodes (c0001-c0022) w...") |
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=Hardware= | =Hardware= | ||
− | :* Head node: ''' | + | :* Head node: '''altas.cac.cornell.edu'''. |
:* Access modes: ssh | :* Access modes: ssh | ||
:* OpenHPC 2.3 with Rocky Linux 8.4 | :* OpenHPC 2.3 with Rocky Linux 8.4 | ||
− | :* | + | :* 4 compute nodes (c0001-c0004) with dual 64-core AMD EPYC 7713 processor, 1 TB of RAM |
:* Hyperthreading is enabled on all nodes, i.e., each physical core is considered to consist of two logical CPUs | :* Hyperthreading is enabled on all nodes, i.e., each physical core is considered to consist of two logical CPUs | ||
− | :* Interconnect is | + | :* Interconnect is 100 Gbps ethernet |
− | :* Submit HELP requests: [https://{{SERVERNAME}}/help help] OR by sending an email to [mailto:help@cac.cornell.edu CAC support] please include | + | :* Submit HELP requests: [https://{{SERVERNAME}}/help help] OR by sending an email to [mailto:help@cac.cornell.edu CAC support] please include Altas in the subject area. |
=File Systems= | =File Systems= |
Revision as of 09:59, 11 November 2021
This is a private cluster.
Hardware
- Head node: altas.cac.cornell.edu.
- Access modes: ssh
- OpenHPC 2.3 with Rocky Linux 8.4
- 4 compute nodes (c0001-c0004) with dual 64-core AMD EPYC 7713 processor, 1 TB of RAM
- Hyperthreading is enabled on all nodes, i.e., each physical core is considered to consist of two logical CPUs
- Interconnect is 100 Gbps ethernet
- Submit HELP requests: help OR by sending an email to CAC support please include Altas in the subject area.
File Systems
Home Directories
- Path: ~
User home directories is located on a NFS export from the head node. Use your home directory (~) for archiving the data you wish to keep. Data in user's home directories are NOT backed up.
Scheduler/Queues
- The cluster scheduler is Slurm. All nodes are configured to be in the "normal" partition with no time limits. See Slurm documentation page for details.
- Remember, hyperthreading is enabled on the cluster, so Slurm considers each physical core to consist of two logical CPUs.
- Partitions (queues):
Name Description Time Limit normal all nodes no limit
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/1.12.1 7) ohpc 2) prun/2.1 4) ucx/1.9.0 6) openmpi4/4.0.5
To show all available modules (as of August 5, 2021):
-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/1.75.0 netcdf/4.7.3 py3-scipy/1.5.1 fftw/3.3.8 opencoarrays/2.9.2 scalapack/2.1.0 hypre/2.18.1 petsc/3.14.4 slepc/3.14.2 mfem/4.2 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 ------------------------- R/4.1.0 impi/2021.3.0 mvapich2/2.3.4 superlu/5.2.1 gdal/3.3.1 impi/2021.3.1 (D) openblas/0.3.7 gsl/2.6 metis/5.1.0 openmpi4/4.0.5 (L) hdf5/1.10.6 mpich/3.3.2-ofi py3-numpy/1.19.0 -------------------------- /opt/ohpc/pub/modulefiles --------------------------- GMAT/R2020a julia/1.6.2 proj/8.1.0 autotools (L) libfabric/1.12.1 (L) prun/2.1 (L) cmake/3.19.4 octave/6.3.0 ucx/1.9.0 (L) gnu9/9.3.0 (L) ohpc (L) valgrind/3.16.1 intel/2021.3.0.3350 os visit/3.2.1 Where: D: Default Module 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 R/4.1.0 -bash-4.2$ module list Currently Loaded Modules: 1) autotools 4) ucx/1.9.0 7) ohpc 2) prun/2.1 5) libfabric/1.12.1 8) openblas/0.3.7 3) gnu9/9.3.0 6) openmpi4/4.0.5 9) R/4.1.0
To unload a module and verify:
-bash-4.2$ module unload R -bash-4.2$ module list Currently Loaded Modules: 1) autotools 3) gnu9/9.3.0 5) libfabric/1.12.1 7) ohpc 2) prun/2.1 4) ucx/1.9.0 6) openmpi4/4.0.5
Install R Packages in Home Directory
If you need a new R package not installed on the system, you can install R packages in your home directory using these instructions.
Manage Modules in Your Python Virtual Environment
python3 (3.6) 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:
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 [...] (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 Intel oneAPI /opt/intel/oneapi/
- module swap gnu9 intel; module swap openmpi4 impi
- includes the HPC Toolkit with Intel MPI and Intel classic compilers (icc, ifort)
GCC 9.3 /opt/ohpc/pub/compiler/gcc/9.3.0/
- module load gnu9/9.3.0 (Loaded by default)
Open MPI 4.0.5 /opt/ohpc/pub/mpi/openmpi4-gnu9/4.0.5
- module load openmpi4/4.0.5 (Loaded by default)
Matlab R2021a /opt/ohpc/pub/apps/matlab/R2021a
- module load matlab/R2021a
Quantum Espresso 6.8 /opt/ohpc/pub/apps/quantum-espresso/6.8
- module load quantum-espresso/6.8
Help
- Submit questions or requests at help or by sending email to: help@cac.cornell.edu. Please include Hopper in the subject area.