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dstools [2024/08/20 10:39] – Didier Barradas Bautistadstools [2024/11/21 07:22] (current) – Didier Barradas Bautista
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 ===== Ibex Starting Pack ===== ===== Ibex Starting Pack =====
  
 +<WRAP center round box important > 
 +===== Access to ibex =====
 +Unless your username is associated with either a Project, Principal Investigator, or a Class, access to ibex resources will be [[https://docs.hpc.kaust.edu.sa/policy/ibex.html#limits-on-unassociated-users|severely constrained]]. To nominate your supervisor, please visit http://my.ibex.kaust.edu.sa . You can check if a PI is defined using the "whoismypi" program on a login node.
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 +To use Ibex resources in any significant way, you must be under the direct supervision of the **Research Faculty or a Director**. From RCAC clarification, it is only professors (full, associate, assistant, and research).
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 +</WRAP>
  
 Welcome to KAUST! As a new user, especially if it's your first time, here are some essential resources to get you started: Welcome to KAUST! As a new user, especially if it's your first time, here are some essential resources to get you started:
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 2. **Ibex Training**: Explore our detailed documentation on various topics, including Data Science, for more comprehensive information. Be sure to check out these wikis: 2. **Ibex Training**: Explore our detailed documentation on various topics, including Data Science, for more comprehensive information. Be sure to check out these wikis:
    - [[https://docs.hpc.kaust.edu.sa/soft_env/prog_env/modulesystem/ibex/index.html|Ibex User Guide]]    - [[https://docs.hpc.kaust.edu.sa/soft_env/prog_env/modulesystem/ibex/index.html|Ibex User Guide]]
 +   - [[https://docs.hpc.kaust.edu.sa/systems/ibex/index.html|Ibex main docs]]
    - [[https://docs.hpc.kaust.edu.sa/soft_env/prog_env/modulesystem/ibex/datascience.html#data-science-on-ibex|Data Science User Guide]]    - [[https://docs.hpc.kaust.edu.sa/soft_env/prog_env/modulesystem/ibex/datascience.html#data-science-on-ibex|Data Science User Guide]]
  
 3. **KAUST Visualization YouTube Channel**: Visit our YouTube channel [[https://www.youtube.com/channel/UCR1RFwgvADo5CutK0LnZRrw|here]] for many tutorials on data science workshops and more. These videos are beneficial, covering the best practices for installing libraries and coding with Ibex. 3. **KAUST Visualization YouTube Channel**: Visit our YouTube channel [[https://www.youtube.com/channel/UCR1RFwgvADo5CutK0LnZRrw|here]] for many tutorials on data science workshops and more. These videos are beneficial, covering the best practices for installing libraries and coding with Ibex.
  
-<WRAP center round box important >  +4. **Python and Conda**: on the subject of managing your environments, we encourage you to install Conda using the official guide [[https://github.com/kaust-rccl/ibex-miniconda-install/tree/master|here]] 
-===== Access to ibex ===== + 
-Unless your username is associated with either a Project, Principal Investigator, or a Class, access to ibex resources will be severely constrained. To nominate your supervisor, please visit http://my.ibex.kaust.edu.sa . You can check if a PI is defined using the "whoismypi" program on a login node. +5. **Jupyter, VsCode and Rstudio**: To deploy your prefered IDE on ibex check the video [[https://youtu.be/88pZEvKAiHY?si=010dJPGtGQQwMu8W|here]]
-</WRAP>+
  
 <WRAP nicebox yellow 98%>  <WRAP nicebox yellow 98%> 
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   * **/home/$USER** - this is your personal home directory and is limited to 200GB of data. ** Do not run HPC jobs in your home directory ** - use it to keep configurations, scripts, etc.   * **/home/$USER** - this is your personal home directory and is limited to 200GB of data. ** Do not run HPC jobs in your home directory ** - use it to keep configurations, scripts, etc.
   * **/ibex/user/$USER** - this is your HPC storage. Use this storage to save the output and input to compute jobs. **This is much faster than your home directory**, so your jobs will run faster. This directory has a limit of 1.5 TB. If you need more storage, contact the Ibex support team.   * **/ibex/user/$USER** - this is your HPC storage. Use this storage to save the output and input to compute jobs. **This is much faster than your home directory**, so your jobs will run faster. This directory has a limit of 1.5 TB. If you need more storage, contact the Ibex support team.
-  * **/tmp** - For specific temporary files, specify this directory. Once your job is finished, all files in this directory will be deleted. Placing job temporary data in this directory will result in higher performance than storing it in your scratch area, won't contribute towards your used quota, and will automatically be deleted when your job finishes.+
 </WRAP> </WRAP>
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 These resources will equip you with the knowledge and skills to maximize your time at KAUST. We hope this docuwiki page is helpful! Please let us know if you have any questions. Happy learning! These resources will equip you with the knowledge and skills to maximize your time at KAUST. We hope this docuwiki page is helpful! Please let us know if you have any questions. Happy learning!
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 <WRAP group> <WRAP group>
-<WRAP center round box important half column > ** Further useful links**+<WRAP center round box half column > ** Further useful links**
  
   * [[https://docs.hpc.kaust.edu.sa/index.html| KSL Support Documentation ]]   * [[https://docs.hpc.kaust.edu.sa/index.html| KSL Support Documentation ]]
-  * ibex@hpc.kaust.edu.sa - email this address to create a service request+  * **ibex@hpc.kaust.edu.sa** - email this address to create a service request
   * https://kaust-ibex.slack.com - Use **#general** for simple queries   * https://kaust-ibex.slack.com - Use **#general** for simple queries
 +</WRAP>
  
  
-/*   * [[https://kaust-supercomputing-lab.atlassian.net/l/cp/nM0wqF7a|Ibex Starting pack]]  */ 
  
  
-</WRAP> 
  
-<WRAP center round box important half column > {{:icon:twbs:link:w-25:h-auto:headset-vr.svg?nolink&}}** KVL Training on Data Science**+<WRAP center round box half column > {{:icon:twbs:link:w-25:h-auto:headset-vr.svg?nolink&}}** KVL Training on Data Science** 
  
   * KVL often runs training on Data Science in collaboration with the KSL. Check out our current and past workshops for more: <wrap button>[[training:overview|Training Events]]</wrap>   * KVL often runs training on Data Science in collaboration with the KSL. Check out our current and past workshops for more: <wrap button>[[training:overview|Training Events]]</wrap>
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