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VM-MAD: A cloud/cluster software for service-oriented academic environments


Aleksiev, Tyanko; Barkow-Oesterreicher, Simon; Kunszt, Peter; Maffioletti, Sergio; Murri, Riccardo; Panse, Christian (2013). VM-MAD: A cloud/cluster software for service-oriented academic environments. In: Supercomputing - 28th International Supercomputing Conference, ISC 2013, Leipzig, 16 June 2013 - 20 June 2013, 447-461.

Abstract

The availability of powerful computing hardware in IaaS clouds makes cloud computing attractive also for computational workloads that were up to now almost exclusively run on HPC clusters.
In this paper we present the VM-MAD Orchestrator software: an open source framework for cloudbursting Linux-based HPC clusters into IaaS clouds but also computational grids. The Orchestrator is completely modular, allowing flexible configurations of cloudbursting policies. It can be used with any batch system or cloud infrastructure, dynamically extending the cluster when needed. A distinctive feature of our framework is that the policies can be tested and tuned in a simulation mode based on historical or synthetic cluster accounting data.
In the paper we also describe how the VM-MAD Orchestrator was used in a production environment at the Functional Genomics Center Zurich to speed up the analysis of mass spectrometry-based protein data by cloudbursting to the Amazon Elastic Compute Cloud. The advantages of this hybrid system are shown with a large evaluation run using about hundred large (EC2) nodes.

Abstract

The availability of powerful computing hardware in IaaS clouds makes cloud computing attractive also for computational workloads that were up to now almost exclusively run on HPC clusters.
In this paper we present the VM-MAD Orchestrator software: an open source framework for cloudbursting Linux-based HPC clusters into IaaS clouds but also computational grids. The Orchestrator is completely modular, allowing flexible configurations of cloudbursting policies. It can be used with any batch system or cloud infrastructure, dynamically extending the cluster when needed. A distinctive feature of our framework is that the policies can be tested and tuned in a simulation mode based on historical or synthetic cluster accounting data.
In the paper we also describe how the VM-MAD Orchestrator was used in a production environment at the Functional Genomics Center Zurich to speed up the analysis of mass spectrometry-based protein data by cloudbursting to the Amazon Elastic Compute Cloud. The advantages of this hybrid system are shown with a large evaluation run using about hundred large (EC2) nodes.

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Additional indexing

Item Type:Conference or Workshop Item (Lecture), refereed, original work
Communities & Collections:04 Faculty of Medicine > Functional Genomics Center Zurich
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Event End Date:20 June 2013
Deposited On:10 Feb 2014 15:45
Last Modified:10 Aug 2017 13:14
Publisher:Springer
ISSN:0302-9743
Additional Information:The original publication is available at www.springerlink.com
Publisher DOI:https://doi.org/10.1007/978-3-642-38750-0_34

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