Difference between revisions of "Eosc/clouds"

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(Created page with "= Background = This page gathers information on the various cloud services that are available within the EOSC-Nordic consortium. In principle, cloud utilization may be of int...")
 
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= NIRD Toolkit =
 
= NIRD Toolkit =
  
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Judging from the [https://drive.google.com/drive/folders/1rsnEx4YScmyqiaqI6I73Okyd4J-mgyg3 demo] and from the [https://apps.sigma2.no/ website], it seems to be mostly used to create Jupyter notebook servers with access to GPU resources.
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In theory, this can be useful for teaching, but no clear benefits come to mind in comparison to regular usage of Saga/Puhti/other HPC machines accessed via SSH. NLP researchers tend to value much more deep-level access to their system environment: a pre-defined set of provided Docker containers with TF or PyTorch will hardly satisfy them.
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This service will probably be more useful to researchers and teachers from humanities, who tend to be less familiar with command line, programming, etc.
  
 
= STACKn =
 
= STACKn =
  
 
= UCLOUD =
 
= UCLOUD =

Revision as of 23:20, 29 November 2020

Background

This page gathers information on the various cloud services that are available within the EOSC-Nordic consortium. In principle, cloud utilization may be of interest to the NLPL user community, even though today all researchers are very comfortable in a batch computing paradigm organized from the command line.

Candidate use cases for cloud resources could be in teaching or hosting of interactive services, like for example the OPUS Corpus Interface or the NLPL Vectors Explorer.

Prior to EOSC-Nordic, parts of the NLPL infrastructure task force (Bjørn Lindi and Stephan Oepen) performed a somewhat superficial assessment of the NIRD Toolkit, which at the time was found to be difficult to take into use (in part because of unclear allocation mechanisms, in part due to authentication barriers for UiO users).


NIRD Toolkit

Judging from the demo and from the website, it seems to be mostly used to create Jupyter notebook servers with access to GPU resources.

In theory, this can be useful for teaching, but no clear benefits come to mind in comparison to regular usage of Saga/Puhti/other HPC machines accessed via SSH. NLP researchers tend to value much more deep-level access to their system environment: a pre-defined set of provided Docker containers with TF or PyTorch will hardly satisfy them.

This service will probably be more useful to researchers and teachers from humanities, who tend to be less familiar with command line, programming, etc.

STACKn

UCLOUD