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Operations research / Scheduling algorithms / Grid computing / Scheduling / Cloud computing / Computer cluster / Meta-scheduling / Computing / Concurrent computing / Planning


Adaptive Co-Allocation of Distributed Resources for Parallel Applications by Marco Aur´elio Stelmar Netto
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Document Date: 2010-02-16 04:42:19

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File Size: 3,74 MB

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City

Melbourne / /

Company

Melbourne Portuguese Speakers Meetup Group / CLOUDS Laboratory / Marco A. S. / Distributed Resources / /

Country

France / Australia / /

Facility

Software Engineering The University of Melbourne / University of Melbourne / CLOUDS Laboratory / /

IndustryTerm

message passing applications / parallel applications / large-scale computing facility / singlecluster applications / message passing model demand processors / inter-cluster network / /

Organization

University of Melbourne / CSSE Department / Philosophy Department of Computer Science / Australian Government / Australian Department of Innovation / Industry / Science and Research / Australian Research Council / /

Person

James Broberg / Khalid Aljasser / Alfredo Goldman / Jia Yu / Ben Horsfall / Shin Yeo / Avelino Zorzo / Rao Kotagiri / Michael Kirley / Kris Bubendorfer / Carlos Queiroz / Rajiv Ranjan / Amir Vahid / Dror Feitelson / Andreas Schutt / Rajkumar Buyya / Dileban Karunamoorthy / Jason Lee / Kyong Hoon Kim / William Voorsluys / Christian Vecchiola / Cesar A. F. De Rose / Trevor Hansen / Carlos Varela / Anton Beloglazov / Adam Barker / Hussein Gibbins / Adrian Pearce / Alexandre di Costanzo / Carly Fatnowna / Angela Morgan / Osmar Norberto de Souza / Krishna Nadiminti / Chao Jin / Nithiapidary Muthuvelu / Mohsen Amini / Stacy Barelos / Marco Aur´elio Stelmar / Rodrigo Calheiros / /

Position

MP / researcher / supervisor / Professor / supervisor / /

ProgrammingLanguage

POV-Ray / /

Technology

message passing model demand processors / /

SocialTag