UFAL AIC mediadb https://aic.ufal.mff.cuni.cz/index.php/Main_Page MediaWiki 1.32.1 first-letter Media Special Talk User User talk UFAL AIC wiki UFAL AIC wiki talk File File talk MediaWiki MediaWiki talk Template Template talk Help Help talk Category Category talk 0 1 139 137 2026-03-21T19:07:31Z Straka 7 /* Access */ wikitext text/x-wiki <div style='text-align: center;'>CZ.02.2.69/0.0/0.0/17_044/0008562</div> <div style='text-align: center;'>Podpora rozvoje studijního prostředí na Univerzitě Karlově - VRR</div> [[File:OP_VVV_logo.jpg|frameless|center|upright=2.5]] == Welcome to AIC == AIC (Artificial Intelligence Cluster) is a computational grid with sufficient computational capacity for research in the field of [https://en.wikipedia.org/wiki/Deep_learning deep learning] using both CPU and GPU. It was built on top of [https://slurm.schedmd.com/ SLURM] scheduling system. MFF students of Bc. and Mgr. degrees can use it to run their experiments and learn the proper ways of grid computing in the process. === Access === AIC is dedicated to UFAL students who will get an account if requested by authorized lector. To change the password, this link is available: https://aic.ufal.mff.cuni.cz/pw-manager There is a restriction on resources allocated by one user in group <code>students</code> at a given time. By default, this is set to a maximum of 30 CPUs and 2 GPUs. === Jupyterlab === AIC provides also Jupyterlab portal on top of your AIC account and HOME directory. It can be found at https://aic.ufal.mff.cuni.cz/jlab . Pre-installed extensions: R, ipython, Rstudio (community), Slurm Queue Manager. === Connecting to the Cluster (directly) === Use SSH to connect to the cluster: ssh LOGIN@aic.ufal.mff.cuni.cz ===== SSH key fingerprints ===== <pre> 256 SHA256:swUTOKfIaSDevXnO9MS6OIqtc71ra7/fvBiG9tHqXJA (ECDSA) 256 SHA256:aba/fvUgJEOz8ERPYDtsu8hOkboitkKSBgTVFcgFLF4 (ED25519) 1024 SHA256:fh1CjkMk04SMNl2+wxPSLuVsNMpuJs+XMoNCNvCkqdU (DSA) 2048 SHA256:JOOHAvJ7jctdzPtPtOEZ+8JFltbv4RpiJm76mBHAjjc (RSA) </pre> === Basic HOWTO === The following HOWTO is meant to provide only a simplified overview of the cluster usage. It is strongly recommended to read some further documentation ([[Submitting_CPU_Jobs|CPU]] or [[Submitting_GPU_Jobs|GPU]]) before running some serious experiments. More serious experiments tend to take more resources. In order to avoid unexpected failures please make sure your [[Quotas|quota]] is not exceeded. '''Rule 0: NEVER RUN JOBS DIRECTLY ON aic.ufal.mff.cuni.cz HEADNODE. Use <code>srun</code> to get computational node shell!''' Suppose we want to run some computations described by a script called <code>job_script.sh</code>: #!/bin/bash #SBATCH -J helloWorld # name of job #SBATCH -p cpu # name of partition or queue (default is cpu) #SBATCH -o helloWorld.out # name of output file for this submission script #SBATCH -e helloWorld.err # name of error file for this submission script # run my job (some executable) sleep 5 echo "Hello I am running on cluster!" We need to ''submit'' the job to the cluster which is done by logging on the submit host <code>aic.ufal.mff.cuni.cz</code> and issuing the command:<br> <code>sbatch job_script.sh</code> This will enqueue our ''job'' to the default ''partition'' (or ''queue'') which is <code>cpu</code>. The scheduler decides which particular machine in the specified queue has ''resources'' needed to run the job. Typically we will see a message which tells us the ID of our job (3 in this example): Submitted batch job 3 The options used in this example are specified inside the script using the ''#SBATCH'' directive. Any option can be specified either in the script or as a command line parameter (see ''man sbatch'' for details). We can specify custom arguments '''before''' the name of the script: sbatch --export=ARG1='firstArg',ARG2='secondArg' job_script.sh These can be accessed in the job script as <code>$ARG1</code> and <code>$ARG2</code>. jewacrxmwv1p6pjqctjpbx5mllu0whw