Difference between revisions of "Draft:Software Installation Policies and Guidelines"

Latest revision as of 18:47, 20 February 2023

Generalized vs Specialized vs Domain Specific environments

Generalized environments like R and Python provide a wide range of functionality for data analysis, machine learning, and other scientific computing tasks. These environments have a large number of libraries and packages available for users to work with.
Specialized environments like PyTorch and TensorFlow are focused on specific machine learning tasks, such as deep learning, and provide specialized tools and libraries to support these tasks.
Domain-specific collections like GeoPython or DJPytt are environments that are tailored to specific domains, such as geospatial data analysis or data journalism.

Recommendations on using our prebuilt environments vs building your own

Using prebuilt environments can be beneficial for users who want to get started quickly and don't need to make customizations to the environment. These environments are usually well-maintained.

Building your own environment can be beneficial if you need control over the environment or want to customize it for your specific needs. However, this can also be more time-consuming and requires more technical expertise.

Prebuilt Environments for Reference

There are many prebuilt environments available for popular libraries and frameworks, such as PyTorch. Users can refer to these environments for guidance on how to build their own environment or use prebuilt containers.

For example, NVIDIA provides a prebuilt PyTorch container that users can use as a starting point for their own environment.

Availabile Linux Software installed in ResVault

ResVault VMs have access to the Linux application installed on HiPerGator in /apps.
To install custom applications into a ResVault VM, please contact support via Cherwell

@@ Line 1: / Line 1: @@
-User login server abuse—what to do?
+==Generalized vs Specialized vs Domain Specific environments==
-*TODO: post a terminator whitelist to #apps and try running it manually before letting it loose via a
+*Generalized environments like R and Python provide a wide range of functionality for data analysis, machine learning, and other scientific computing tasks. These environments have a large number of libraries and packages available for users to work with.
-*The login nodes might be big enough that we have a large gap between the resources cgroups_py tries to keep available and our login policy.
+*Specialized environments like PyTorch and TensorFlow are focused on specific machine learning tasks, such as deep learning, and provide specialized tools and libraries to support these tasks.
-*Describe the functionality of the main R and python environments vs more specific environments like pytorch and tensorflow or domain-specific collections like geopython or DJppytt)Q0
+*Domain-specific collections like GeoPython or DJPytt are environments that are tailored to specific domains, such as geospatial data analysis or data journalism.
+==Recommendations on using our prebuilt environments vs building your own==
+Using prebuilt environments can be beneficial for users who want to get started quickly and don't need to make customizations to the environment. These environments are usually well-maintained.
+*Building your own environment can be beneficial if you need control over the environment or want to customize it for your specific needs. However, this can also be more time-consuming and requires more technical expertise.
+===Prebuilt Environments for Reference===
+There are many prebuilt environments available for popular libraries and frameworks, such as PyTorch. Users can refer to these environments for guidance on how to build their own environment or use prebuilt containers.
+*For example, NVIDIA provides a prebuilt PyTorch container that users can use as a starting point for their own environment.
-TODO: write a help page on software installation guidelines, use expectations, and limits.
+==Availabile Linux Software installed in ResVault==
-* Recommendations on using our prebuilt e.nys vs building their own in the context of speed of customization vs. maintaining functional environments. Focus on R and python at first.
+* ResVault VMs have access to the Linux application installed on HiPerGator in /apps.
-* Curated list of prebuilt environments for users to reference in the context of the above recommendations.
+* To install custom applications into a ResVault VM, please contact support via [https://my.it.ufl.edu/ Cherwell]
-* Published environment.yml files for the popular environments like pytorch, which users could refer to when starting to build their or use prebuilt containers
+__NOTOC__
-**e.g. pytorch container from NVIDIA.
-* Availability of the linux software installed in lapps in ResVault.