Grant: Research Tools and Instruments
Simon Fraser University
$148,408.00
Computational Infrastructure for Online Big Data Analytics
EF 2015-16
Résumé
Online analytics on Big Data enables many novel applications. Online Big Data analytics is a strategic research direction at SFU, and one of the established strengths at the School of Computing Science. However, we do not have a state-of-the-art data intensive computing infrastructure to support the further development of this research direction. This is an urgent bottleneck for our research groups and our HQP training programs.
In this proposal, we request a state-of-the-art cluster of computer servers that are comparable to what currently employed by mainstream industry companies, which have large main memory (TB), high-speed Flash-based storage, and high bandwidth Infiniband interconnect. This data intensive computing infrastructure will immediately and directly support a series of Big Data analytics projects led by the PI and co-PIs, including developing algorithms and tools for online analytics on Big Data, Big Data system optimization and management, and cleaning Big Data and crowdsourcing. As currently large memory computers (1Terrabyte+) form the core infrastructure of most companies as data analytics is being deployed widely, for research results derived by our research groups to be applicable and relevant to state-of-the-art our groups need to study the applications on the large-memory systems similar to those deployed by the industry widely. Currently there are no large-memory computers either as part of the School of Computing Science or RCG computing group at SFU.
The requested infrastructure will immediately support the HQP training of graduate students in three groups that complement each other and form an interdisciplinary research cluster. and more in the near future. These computers requested are also essential to support the courses that are being taught as part of the current School of Computing Science curriculum and the recently introduced professional masters program in “Big Data”.
Programme
Research Tools and Instruments
Bénéficiaire
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RTI-2016-00408
Name nom
Pei, Jian
Department département
Computing Science, School of - Computing Science, School of
Organization id
5
Institution établissement
Simon Fraser University
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2015
Competition year année de concours
2016
Award amount
148408
Program id
RTI
Program name en
Research Tools and Instruments
Program name fr
Outils et instruments de recherche
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1607
Committee name en
Computer, Mathematical and Statistical Sciences (RTI)
Committee name fr
Sciences informatiques, mathématiques et statistiques (OIR)
Area of application code
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
2711
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Database management
Research subject fr
Gestion de bases de données
Partie
1
Nb partie
1
Application title
Computational Infrastructure for Online Big Data Analytics
Keyword
NSERC
Application summary
<p>Online analytics on Big Data enables many novel applications. Online Big Data analytics is a strategic research direction at SFU, and one of the established strengths at the School of Computing Science. However, we do not have a state-of-the-art data intensive computing infrastructure to support the further development of this research direction. This is an urgent bottleneck for our research groups and our HQP training programs. </p>
<p>In this proposal, we request a state-of-the-art cluster of computer servers that are comparable to what currently employed by mainstream industry companies, which have large main memory (TB), high-speed Flash-based storage, and high bandwidth Infiniband interconnect. This data intensive computing infrastructure will immediately and directly support a series of Big Data analytics projects led by the PI and co-PIs, including developing algorithms and tools for online analytics on Big Data, Big Data system optimization and management, and cleaning Big Data and crowdsourcing. As currently large memory computers (1Terrabyte+) form the core infrastructure of most companies as data analytics is being deployed widely, for research results derived by our research groups to be applicable and relevant to state-of-the-art our groups need to study the applications on the large-memory systems similar to those deployed by the industry widely. Currently there are no large-memory computers either as part of the School of Computing Science or RCG computing group at SFU. </p>
<p>The requested infrastructure will immediately support the HQP training of graduate students in three groups that complement each other and form an interdisciplinary research cluster. and more in the near future. These computers requested are also essential to support the courses that are being taught as part of the current School of Computing Science curriculum and the recently introduced professional masters program in “Big Data”. </p>
