#Links
#All the course material:
#https://fs.hlrs.de/projects/par/events/2024/dl-hlrs/

#https://pillow.readthedocs.io/en/stable/
#https://scikit-learn.org
#https://keras.io/api/models/
#https://www.tensorflow.org/resources/models-datasets

#https://www.deeplearningbook.org/ 
#@book{Goodfellow-et-al-2016,
#    title={Deep Learning},
#    author={Ian Goodfellow and Yoshua Bengio and Aaron 
#    Courville},
#    publisher={MIT Press},
#    note={\url{http://www.deeplearningbook.org}},
#    year={2016}

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Training Cluster - training.hlrs.de 

#Data location on Training Cluster:
/shared/akad-dl-hlrs/day2 
----------------------------------------------------------------------

Day2 - Deep Learning

# Commands 1 

# username: sca515<NO>*; *<NO> = Number: See sticker on laptop

ssh username@training.hlrs.de
or
ssh -i /home/username/.ssh/id_ed25519 username@training.hlrs.de

# Commands 2
# For a new ws 
ws_allocate wsday2 15

ws_list
MYSCR=$(ws_find wsday2)
cd $MYSCR

# Commands 3
cp /shared/akad-dl-hlrs/day2/data.tar.gz .
cp /shared/akad-dl-hlrs/day2/work_data_50.tar.gz .
cp /shared/akad-dl-hlrs/day2/notebooks.tar.gz .
cp /shared/akad-dl-hlrs/day2/solutions.tar.gz .

tar -zxvf data.tar.gz
tar -zxvf work_data_50.tar.gz
tar -zxvf notebooks.tar.gz

# To display the directory structure in a tree-like format
tree

# Commands 4
# To start Jupyter Notebook (JN) on compute node:

ssh username@training.hlrs.de -D 8080 -q

#Reserve compute node option as provided for the day1 (attenton: course queue )

qsub -I -l select=1:node_type=skl:mem=12gb,walltime=09:00:00 -q smp

#Locate your ws for day2
MYSCR=$(ws_find wsday2)
cd $MYSCR

#For working environment on compute node

. notebooks/modules.sh

#Copy URL link to your browser-Profil
 http://n081501:8888/?token=.....

# Commands 5
# To find the current path:
pwd

# To find the workspace path in Vulcan:
ws_list

# To copy a folder to a local directory (from a local terminal):

scp -r username@training.hlrs.de:/path/to/workspace/and/folder /path/to/local/destination

Cat output.txt
head -n 30 output.txt
tail output.txt

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Vulcan Cluster - vulcan.hww.hlrs.de

#Data location on Vulcan Cluster:
/lustre/nec/ws3/ws/hpckkakh-exchangews/wsday2

#Computing Time on Vulcan Cluster:
qsub -I -q R_DL -l select=1:node_type=hsw:mem=100gb,walltime=09:00:00
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