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From "Suresh Marru (JIRA)" <>
Subject [jira] [Closed] (AIRAVATA-357) [GSoC] Provide cloud bursting like capabilities to Airavata computational workflows integrating with Apache Whirr
Date Sat, 23 Mar 2013 12:33:15 GMT


Suresh Marru closed AIRAVATA-357.

    Resolution: Fixed

Closing this tasks, since the project was executed successfully. Key architectural recommendations
have been contributed back. To finish of the gsoc contributions (whirr integration to trunk),
please create a new jira with precise tasks. 
> [GSoC] Provide cloud bursting like capabilities to Airavata computational workflows integrating
with Apache Whirr
> -----------------------------------------------------------------------------------------------------------------
>                 Key: AIRAVATA-357
>                 URL:
>             Project: Airavata
>          Issue Type: New Feature
>          Components: GFac, Workflow Interpreter, XBaya
>            Reporter: Suresh Marru
>            Assignee: Milinda Lakmal Pathirage
>              Labels: gsoc2012, mentor
>             Fix For: WISHLIST
>         Attachments: hadoop-provider-partial-30-06-2012.patch
> Apache Airavata provides capabilities to construct execute and monitor computational
workflows with built in providers to execute applications on compute intensive resources.
The users of Airavata constantly have the need to execute workflows which have tasks with
a hybrid combination of computational grids and computational clouds. More over, some applications
can be executed on multiple types of resources. The selection will depend on the distribution
of data to be processed, the tolerable latency on shared batch queued grid clusters, and on
the nature and size of the problem to be solved and data analysis tasks. Especially for applications
which reduce the data as they proceed in the graph, they better fit for local map-reduce executions
residing on hadoop based file systems.
> This idea has two implementation paths:
> Firstly extend airavata workflow providers to integrate with cloud based run times. Integrating
with higher level API's like Apache Whirr provides a great value addition to this project
to encompass multiple cloud services. 
> Secondly, extending Airavata enactment called Workflow Interpreter so a component in
the workflow is capable of initially running on local clusters deploying hadoop file systems
and if the execution is saturating the local resources, the executions can scale out to commercial
on-demand clouds or leverage high speed low latency interconnects on computational grids.
This scaling technique is often referred to as Cloud Bursting. This project will not only
enable this capability to Airavata workflow. 
> User community & Impact of the software: Airavata is primarily targeted to build
science gateways using computational resources from various disciplines. The initial targeted
set of gateways include projects supporting research and education in chemistry, life sciences,
biophysics, environmental sciences, geosciences astronomy and nuclear physics. The goal of
airavata is to enhance productivity of these gateways to utilize cyberinfrastructure of resources
(e.g., local lab resources, the Extreme Science and Engineering Discovery Environment (XSEDE),
the Open Science Grid (OSG), University Clusters, Academic and Commercial Computational Clouds
like FutureGrid & Amazon EC2). By using open community based software components and services
like Airavata, gateways will be able to focus on providing additional scientific capabilities
and to expanding the number of supported users. The capabilities of these gateways will offer
clear benefits to society.

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