ibisco HPC Wiki

User Tools

Site Tools

Trace: • manuals • guida_di_utilizzo • lista_sw • archit_ib • manualistica • uso_sist • docssugg_ut • domrisp_utadm • archit_ib_en • user_guide
wiki:user_guide

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision 		Previous revision
wiki:user_guide [2022/05/06 14:41]
phegde 		wiki:user_guide [2022/05/28 18:18] (current)
cnr-guest [Job preparation ans submission]
Line 101: Line 101:
 Complete documentation is avalailable at ''https://slurm.schedmd.com/''. Complete documentation is avalailable at ''https://slurm.schedmd.com/''.
  
-SLUR is an open source software sytstem for cluster management; it is highly scalable and  integrates fault-tolerance and job scheduling mechanisms. +SLURM is an open source software sytstem for cluster management; it is highly scalable and  integrates fault-tolerance and job scheduling mechanisms. 
  
 ==== SLURM basic concepts ==== ==== SLURM basic concepts ====
Line 327: Line 327:
 #SBATCH --nodes=[nnodes]           #number of nodes #SBATCH --nodes=[nnodes]           #number of nodes
 #SBATCH --ntasks-per-node=[ntasks per node] #number of cores per node #SBATCH --ntasks-per-node=[ntasks per node] #number of cores per node
-#SBATCH --gres=gpu:[ngpu]        #number of GPUs per node+#SBATCH --gres=gpu:[ngpu]        #number of GPUs per node</code>
  
 === Example of parallel jobs submission === === Example of parallel jobs submission ===
Line 339: Line 339:
 #SBATCH --ntasks-per-node=[ntasks per node]  #number of cores per node #SBATCH --ntasks-per-node=[ntasks per node]  #number of cores per node
 #SBATCH --gres=gpu:[ngpu]         #number of GPUs per node #SBATCH --gres=gpu:[ngpu]         #number of GPUs per node
-NPROC=                      #number of parallel codes to be run+NPROC=[nprocesses]                     #number of processing units to be accessed
  
 tmpstring=tmp               #temporary files generated  tmpstring=tmp               #temporary files generated 
Line 358: Line 358:
    * Parallelization can be implemented within the python code itself. For example, the evaluation of a function for different variable values can be done in parallel. Python offers many packages to parallelize the given process. The basic one among them is [[https://docs.python.org/3/library/multiprocessing.html|multiprocessing]].     * Parallelization can be implemented within the python code itself. For example, the evaluation of a function for different variable values can be done in parallel. Python offers many packages to parallelize the given process. The basic one among them is [[https://docs.python.org/3/library/multiprocessing.html|multiprocessing]]. 
  
-   * The keras module in tensorflow which is mainly used for machine learning detects the GPUs automatically. +   * The keras and Pytorch modules in tensorflow which are mainly used for machine learning detects the GPUs automatically. 
  
    
wiki/user_guide.1651848085.txt.gz · Last modified: 2022/05/06 14:41 by phegde

Page Tools

Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Share Alike 4.0 International
CC Attribution-Share Alike 4.0 International Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki