Accessing the cluster
NB! To access the cluster, user must have an active Uni-ID account, for this palease contact to us by email (email@example.com) or webpage. In the case of using licensed programs, the user must also be added to the appropriate group. More about available programs and licenses can be found here.
The login-node of the cluster can be reached by SSH. SSH (the Secure SHell) is available using the command
ssh in Linux/Unix, Mac and Windows-10. A guide for Windows users using PuTTY (an alternative SSH using a graphical user interface (GUI)) is here.
For accessing the cluster base.hpc.taltech.ee:
The cluster is accessible form inside the university and from major Estonian network providers. If you are traveling (or not on one of the major networks), the access requires either EduVPN/OpenVPN/FortiVPN (a config for manual configuration of OpenVPN can be generated at https://eduvpn.taltech.ee)or the use of a two-step login using a jump-host:
ssh -l uni-ID@intra.ttu.ee proksi.intra.ttu.ee ssh uni-ID@base.hpc.taltech.ee
For using graphical applications add the
-X switch to the SSH command, and for GLX (X Window System) forwarding additionally the
-Y switch, so to be able to start a GUI program that uses GLX the connection command would be:
ssh -X -Y uni-ID@base.hpc.taltech.ee
NB! The login-node is for some light interactive analysis, do not do heavy computations here. For heavy computations, request a (interactive) session on a compute node from the resource manager/scheduler SLURM!
SSH fingerprints of host-keys
SSH key fingerprint is a security feature for easy identification/verification of the host user is connecting to. This option allows to connect to the server without a password. On first connect, user is shown a fingerprint of a host-key, and asked if it should be added to the list of known hosts.
Please compare the fingerprint to the ones below, if one matches, the host can be added, if the fingerprint does not match, then there is a problem (e.g. man-in-the-middle-attack).
SSH host keys of our servers
Structure and file tree
By accessing the cluster, the user gets into his home directory or
In the home directory, the user can create, delete, and overwrite files and perform calculations (if slurm script does not force program to use
$SCRATCH directory). The home directory is limited in size of 2 TB.
NB! HPC is not intended for data storage and does not make regular backups of user’s data.
The home directory can be accessed from console or by GUI programs, but it cannot be mounted. For mounting was created special
smbgroup folders (
/gpfs/mariana/smbgroup//, respectively). More about
smb folders can be found here.
Some programs and scripts suppose that files will be transfer to
$SCRATCH directory. In this case user needs to know at which node this job was running, to connect to exactly this node (in example it is green11).
$SCRATCH directory will be in
srun -w green11 --pty bash cd /state/partition1/
Please note that the scratch is not shared between nodes, so parallel MPI jobs that span multiple nodes cannot access each other’s scratch files.
Running jobs with the SLURM
SLURM is a management and job scheduling system at Linux clusters. SLURM quick reference can be found here.
Examples of slurm scripts are usually given on the program’s page with some recommendations for optimal use of resources for this particular program.
srun- to start a session or an application (in real time)
sbatch- to start a computation using a batch file (submit for later execution)
squeue- to check the load of the cluster and status of own jobs
sinfo- to check the state of the cluster and partitions
scancel- to delete a submitted job (or stop a running job)
For more parameters see the man-pages (manual) of the commands
squeue. For this use the command
man followed by the program-name whose manual you want to see, e.g.:
Requesting resources with SLURM can be done either with parameters to
srun or in a batch script invoked by
default memory - is 1 GB/thread (for larger jobs request more memory)
short partition default time limit is 10 min and max time limit is 4 hours (longer jobs need to be submitted to partitions common or one of the infiniBand partitions)
common partition default time is 10 min and max time limit is 15 days (for longer jobs implement a restart feature and submit dependent jobs)s
Requesting an interactive session (longer than 10 min, here 1 hour):
srun -t 01:00:00 --pty bash
This logs you into one of the compute nodes, there you can load modules and run interactive applications, compile your code, etc.
srun is reccomended to use CLI (command-line interface) instead of GUI (Graphical user interface) programs if it is possible. For example, use octave-cli or octave instead of octave-gui.
Running a simple non-interactive single process job that lasts longer than 4 hours:
srun --partition=common -t 05:00:00 -n 1 ./a.out
NB! Environment variables for OpenMP are not set automatically, e.g.
srun -N 1 --cpus-per-task=28 ./a.out
would not set
OMP_NUM_THREADS to 28, this has to be done manually. So usually, for parallel jobs it is recommended to use scripts for
Below is given an example of batch slurm script (filename:
myjob.slurm) with explanation of the commands.
#!/bin/bash #SBATCH --partition=common ### Partition #SBATCH --job-name=HelloOMP ### Job Name -J #SBATCH --time=00:10:00 ### WallTime -t #SBATCH --nodes=4 ### Number of Nodes -N #SBATCH --ntasks-per-node=7 ### Number of tasks (MPI processes) #SBATCH --cpus-per-task=4 ### Number of threads per task (OMP threads) #SBATCH --account=hpcrcf ### In case of several accounts, specifies account used for job submission #SBATCH --mem-per-cpu=100 ### Min RAM required in MB #SBATCH --array=13-18 ### Array tasks for parameter sweep export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK ### setup environment module load gcc ### setup environment ./hello_omp $SLURM_ARRAY_TASK_ID ### only for arrays, setup output files with system information mpirun -n 28 ./hello_mpi ### run program
In this example are listed some of the more common submission parameters. There are many more possible job-submission options, moreover, some of the options listed above are not useful to apply together. An explanation of the variables used inside SLURM/SBATCH can be found here. In contrast to e.g. GridEngine, SLURM allows fine-grained resource requests, using parameters like
a single process job
an OpenMP parallel job
an MPI parallel job (OpenFOAM)
an array (parameter sweep) job
a GPU job
a job using the scratch partition (sequential or OpenMP parallel)
The job is then submitted to SLURM by
and will be executed when the requested resources become available.
Output of applications that would normally be written to
STDOUT is written to a file, also error messages are written to a file (default output file is
slurm-$job_id.log). More about SLURM finished job statistics can be found here.
Monitoring jobs & resources
Monitoring a job on the node
Status of jobs, whether they are running or not, and on which node can be seen with the command:
squeue -u <username>
You can check the load of the node your job runs on, its status and configuration by using
scontrol show node <nodename>
the load should not exceed the number of hyperthreads (CPUs in SLURM notation) of the node.
In case of MPI parallel runs statistics of several nodes can be monitored by specifying nodes names. For example:
scontrol show node=green[25-26]
It is possible to submit a second (this time) interactive job to the node where the main job is running, check with
squeuewhere your job is running, then submit
srun -w <nodename> --pty htop
Note that there must be free slots on the machine, so if you cannot use
--exclusivefor your main job (use
To monitor GPUs, you can use
srun -w <nodename> --pty watch nvidia-smi
An alternative method on Linux computers, if you have X11. Logging to base/amp with
ssh --X UniID@base.hpc.taltech.ee
then submit your main interactive job
srun --x11 -n <numtasks> --cpus-per-task=<numthreads> --pty bash
and start an
xterm -e htop & in the session.
sbatch the option
--x11=batch can be used, note that the ssh session to vase needs to stay open!
Monitoring resource usage
Default disc quotas for both
smbhome are 2 TB per user. For
smbgroup there is no limits. You can monitor you resource usage by
Current disk usage:
CPU usage during last day:
sreport -t Hours cluster UserUtilizationByAccount Users=$USER
CPU usage in specific period:
sreport -t Hours cluster UserUtilizationByAccount Users=$USER start=2021-01-01T00:00:00 end=2022-02-01T00:00:00
end= can be changed depending on the desired period of time.
Copying data to/from the clusters
You can copy your data to the cluster by using
scpis available on all Linux systems, Mac and Windows10 PowerShell. There are also GUI versions available for different OS (like PuTTY).
Copying to the cluster with
scp local_path_from_where_to_copy_file/file_name firstname.lastname@example.org:path_to_where_to_save
Copying from the cluster with
scp email@example.com:path_from_where_to_copy/file_name local_path_to_where_to_save
Path to the file at HPC can be checked by
sftpis the secure version of the
ftpprotocol. This command starts a session, in which files can be transmitted in both directions using the
putcommands. File transfer can be done in “binary” or “ascii” mode, conversion of line-endings (see below) is automatic in “ascii” mode. There are also GUI versions available for different OS (FileZilla, gFTP and WinSCP (Windows))
sshfscan be used to temporarily mount remote filesystems for data transfer or analysis. The data is tunneled through an ssh-connection. Be sware that this is usually not performant and can creates high load on the login node due to ssh-encryption.
sshfs firstname.lastname@example.org:remote_dir/ /path_to_local_mount_point/
rsynccan update files if previous versions exist without having to transfer the whole file. However, its use is recommended for the advanced user only, since one has to be careful with the syntax.
SMB/CIFS exported filesystems
One of the simple and convenient ways to control and process data based on HPC is mounting. Mounting means that user attaches his directory placed at HPC to a directory on his computer and can process files as if they were on this computer. These can be accessed from within university or from EduVPN.
Each user automatically has a directory within
smbhome. It does not match with
$HOME directory, so calculations should be initially done at
smbhome directory to prevent copying or files needed should be copied from
home directory to the
smbhome directory by commands:
pwd ### look path to the file cp path_to_your_file/your_file /gpfs/mariana/smbhome/$USER/ ### copying
To get a directory for group access, please contact us (a group and a directory need to be created).
The HPC center exports two filesystems as Windows network shares:
|local path on cluster||Linux network URL||Windows network URL|
|/gpfs/mariana/home/$USER||not exported||not exported|
This is the quick-access guide, for more details, see here
The shares can be found using the Explorer “Map Network Drive”.
server >>> \\smb.hpc.taltech.ee\smbhome username >>> INTRA\<uni-id>
net use \\smb.hpc.taltech.ee\smbhome /user:INTRA\uni-id get-smbconnection
On Linux with GUI Desktop, the shares can be accessed with the nautilus browser.
From commandline, the shares can be mounted as follows:
dbus-run-session bash gio mount smb://smb.hpc.taltech.ee/smbhome/
you will be asked for “User” (which is your UniID), “Domain” (which is “INTRA”), and your password.
To disconnect from the share, unmount with
gio mount -u smb://smb.hpc.taltech.ee/smbhome/
Special considerations for copying Windows - Linux
Microsoft Windows is using a different line ending in text files (ASCII/UTF8 files) than Linux/Unix/Mac: CRLF vs. LF When copying files between Windows-Linux, this needs to be taken into account. The FTP (File Transfer Protocol) has ASCII and BINARY modes, in ASCII-mode the line-end conversion is automatic.
There are tools for conversion of the line-ending, in case the file was copied without line conversion:
fromdos, the stream-editor
sed can also be used.