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how_do_i [2022/03/03 19:38] – [Using Python] deadlinehow_do_i [2025/10/09 16:33] (current) – [Use TensorFlow] deadline
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 This page include answers to many of the commonly asked questions about the cluster. Please send any questions you may have to ''deadline@basement-supercomputing.com'' For a faster response use DSL in the subject line.  This page include answers to many of the commonly asked questions about the cluster. Please send any questions you may have to ''deadline@basement-supercomputing.com'' For a faster response use DSL in the subject line. 
  
 +==== Request Library or Application ====
 +
 +As a valid user with a login account, you may request libraries (i.e. Python libraries) or an application to be installed on the DSL cluster. Keep in mind not all libraries/applications can be installed due to compatibility issues. 
 +
 +
 +<form>
 +Action mail deadline@eadline.org,sjagannathan@saintpeters.edu
 +Thanks "Thanks for your submission."
 +
 +Fieldset "Need Help with Library or Applications?"
 +Textbox  "Name (first/ last)" "=Your Name"
 +Textbox "Your Login"  "=Login"
 +email "Your E-Mail Address" "=Email Address"
 +
 +textarea "Ask General Questions or Request Library/Application do you need?"
 +static "**Please do not submit bugs or operational issues here**"
 +submit "Submit Query"
 +</form>
 ==== Transfer Files To/From the Cluster ==== ==== Transfer Files To/From the Cluster ====
 (14-Feb-2022) (14-Feb-2022)
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 === Run Anaconda Navigator on Your Laptop === === Run Anaconda Navigator on Your Laptop ===
  
-You will need to be on the campus wireless for this to work. It will not  +You will need to be on the campus wireless network for this procedure to work. General internet access is not available. The following procedure is run from the command line.
-work from the Internet.+
  
-1. Log into your account using on the cluster using MobaXterm ssh on MobaXterm+1. Log into your account using on the cluster using [[http://mobaxterm.mobatek.net|MobaXterm]] (see above) 
  
-2. run the following:+  $ ssh dsl.saintpeters.edu
  
-  jupyter-notebook --generate-config+2. Once logged in, run the following:
  
-3. Edit the file (use vi or nano):+  $ jupyter-notebook --generate-config
  
-  nano .jupyter/jupyter_notebook_config.py+3. Edit the config file (use ''vi'' or ''nano''): 
 + 
 +  $ nano .jupyter/jupyter_notebook_config.py
  
 4. Change this line: 4. Change this line:
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    #c.NotebookApp.ip = 'localhost'    #c.NotebookApp.ip = 'localhost'
  
-5. to the following (note remove "#") and exit:+5. To the following (note remove "#") save and exit:
  
    c.NotebookApp.ip = '127.0.0.1'    c.NotebookApp.ip = '127.0.0.1'
  
-6. Now run from MobaXterm+6. Now run from MobaXterm command line:
  
-  anaconda-navigator+  $ anaconda-navigator
  
  
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 **Note:** Python Keras and Tensorflow can be used on any workstation, Only three workstations have GPUs (limulus7-tf, limulus8-tf, limulus9-tf), however both Keras and Tensorflow will run without using a GPU (applications will run slower). **Note:** Python Keras and Tensorflow can be used on any workstation, Only three workstations have GPUs (limulus7-tf, limulus8-tf, limulus9-tf), however both Keras and Tensorflow will run without using a GPU (applications will run slower).
 +
 +**Testing:** You can test tensorflow using the following: (on limulus7-tf, limulus8-tf, limulus9-tf)
 +
 +<code>
 +$ use_conda
 +$ python   /opt/cluster/public/apps/testing/test-cuda.py 
 +
 +Num CPUs Available:  1
 +Num GPUs Available:  1
 +</code>
 +
 +GPUs will be present on limulus7-tf, limulus8-tf, limulus9-tf, all otheer nodes will show just one CPU.
 +
 +**GPU Monitoring:** You can use ''nvidia-smi'' to monitor the GPU. You must be logged into the GPU system.
 +
 +<code>
 +$nvidia-smi 
 +Thu Oct  9 12:12:01 2025       
 ++-----------------------------------------------------------------------------+
 +| NVIDIA-SMI 520.61.05    Driver Version: 520.61.05    CUDA Version: 11.8     |
 +|-------------------------------+----------------------+----------------------+
 +| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
 +| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
 +|                               |                      |               MIG M. |
 +|===============================+======================+======================|
 +|   0  NVIDIA GeForce ...  Off  | 00000000:01:00.0 Off |                  N/A |
 +| 28%   29C    P8     5W / 180W |      0MiB /  8192MiB |      0%      Default |
 +|                               |                      |                  N/A |
 ++-------------------------------+----------------------+----------------------+
 +                                                                               
 ++-----------------------------------------------------------------------------+
 +| Processes:                                                                  |
 +|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
 +|        ID   ID                                                   Usage      |
 +|=============================================================================|
 +|  No running processes found                                                 |
 ++-----------------------------------------------------------------------------+
 +</code>
how_do_i.1646336290.txt.gz · Last modified: 2022/03/03 19:38 by deadline
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