Tashi: location-aware cluster management

Authors:
Michael A. Kozuch;Michael P. Ryan;Richard Gass;Steven W. Schlosser;David O'Hallaron;James Cipar;Elie Krevat;Julio López;Michael Stroucken;Gregory R. Ganger
Affiliations:
Intel Research Pittsburgh, Pittsburgh, PA, USA;Intel Research Pittsburgh, Pittsburgh, PA, USA;Intel Research Pittsburgh, Pittsburgh, PA, USA;Intel Research Pittsburgh, Pittsburgh, PA, USA;Intel Research Pittsburgh, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA
Venue:
ACDC '09 Proceedings of the 1st workshop on Automated control for datacenters and clouds
Year:
2009

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Abstract

Big Data applications, those that require large data corpora either for correctness or for fidelity, are becoming increasingly prevalent. Tashi is a cluster management system designed particularly for enabling cloud computing applications to operate on repositories of Big Data. These applications are extremely scalable but also have very high resource demands. A key technique for making such applications perform well is Location-Awareness. This paper demonstrates that location-aware applications can outperform those that are not location aware by factors of 3-11 and describes two general services developed for Tashi to provide location-awareness independently of the storage system.