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Containerized Jupyter Notebooks for HPCs
Submission navigation links for Knowledge Base Resources
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Submission information
Submission Number:
331
Submission ID:
4851
Submission UUID:
72778b9d-ac7c-400c-9fee-d1c4d58dab4a
Submission URI:
/form/resource
Created:
Thu, 10/10/2024 - 08:47
Completed:
Thu, 10/10/2024 - 08:50
Changed:
Sat, 10/12/2024 - 18:48
Remote IP address:
103.131.14.13
Submitted by:
Sanjeev Chauhan
Language:
English
Is draft:
No
Webform:
Knowledge Base Resources
Approved
Yes
Title
Containerized Jupyter Notebooks for HPCs
Category
Learning
Tags
cloud
,
cloud-computing
,
openstack
,
scratch
,
data-management
,
data-reproducibility
,
github
,
workflow
,
open-ondemand
,
administering-hpc
,
configuration-automation
,
hpc-getting-started
,
hpc-tools
,
deployment
,
scripting
,
conda
,
jupyterhub
,
programming-best-practices
,
python
,
mpi
,
containers
,
docker
,
singularity
Skill Level
Intermediate
Description
This tutorial demonstrates how to create, manage, and deploy containerized Jupyter simulations for High-Performance Computing (HPC) environments, specifically using SLAC's S3DF infrastructure. By utilizing Apptainer (formerly Singularity) containers, users can package complex simulations with all necessary dependencies, input files, and configurations, ensuring reproducibility and ease of use for new users. The automated workflows, powered by GitHub Actions, handle building and updating the containers, while Open OnDemand provides an accessible interface for running Jupyter notebooks directly from the HPC environment. This approach eliminates setup errors, saves time, and ensures consistent simulation environments, enabling researchers to focus on their work instead of system configuration.
Link to Resource
Containerized Jupyter Notebooks for HPCs
Domain
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