https://github.com/uzh/vm-mad
Dynamically grow or shrink GridEngine clusters using cloud-based nodes
https://github.com/uzh/vm-mad
cloud cloudbursting grid orchestrator
Last synced: 6 months ago
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Dynamically grow or shrink GridEngine clusters using cloud-based nodes
- Host: GitHub
- URL: https://github.com/uzh/vm-mad
- Owner: uzh
- License: apache-2.0
- Created: 2015-05-19T11:11:06.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2017-02-24T16:56:53.000Z (almost 9 years ago)
- Last Synced: 2025-06-07T15:49:04.333Z (7 months ago)
- Topics: cloud, cloudbursting, grid, orchestrator
- Language: Python
- Homepage: https://arxiv.org/abs/1302.2529
- Size: 2.26 MB
- Stars: 3
- Watchers: 21
- Forks: 2
- Open Issues: 8
-
Metadata Files:
- Readme: README.rst
- License: LICENSE.txt
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README
========================================================================
VM-MAD
========================================================================
.. This file follows reStructuredText markup syntax; see
http://docutils.sf.net/rst.html for more information
This is a repository of the code produced by the VM-MAD project,
funded by the SWITCH AAA scheme.
The aim of VM-MAD is to provide mechanisms for running scientific
applications on virtualized infrastructures (clouds). In detail,
VM-MAD consists of the following components:
* a repository of VM images and associated metadata;
* a Python library to control the full lifetime of a VM instance on different cloud backends;
* an "orchestrator" component to extend SGE/OGS clusters with virtualized compute nodes;
* command-line tools to access the basic functionality of the above
components.
Installation instructions and further reading
=============================================
For up-to-date information, please visit the VM-MAD repository at:
http://github.com/uzh/vm-mad/
Installation instructions are in the ``INSTALL.txt`` file (in this
same directory), or read them online at:
https://github.com/uzh/vm-mad/blob/master/doc/install.txt
A general description of the project is available through https://arxiv.org/abs/1302.2529.
.. References
.. _VM-MAD: http://github.com/uzh/vm-mad/
.. arXiv: https://arxiv.org/abs/1302.2529
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