Exploiting bounded staleness to speed up big data analytics

Proceedings of the 2014 USENIX Annual Technical Conference, USENIX ATC 2014

Volumn , Issue , 2014, Pages 37-48

  Cui, Henggang ^a   Cipar, James ^a   Ho, Qirong ^a   Kim, Jin Kyu ^a   Lee, Seunghak ^a   Kumar, Abhimanu ^a   Wei, Jinliang ^a   Dai, Wei ^a   Ganger, Gregory R ^a   Gibbons, Phillip B ^b   Gibson, Garth A ^a   Xing, Eric P ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b Intel Labs

Author keywords

[No Author keywords available]

Indexed keywords

BIG DATA; DATA ANALYTICS; ITERATIVE METHODS; MACHINE LEARNING;

'CURRENT; CONSISTENCY MODEL; DATA ANALYTICS; DISTRIBUTED THREAD; IMPROVE PERFORMANCE; INPUT DATAS; MACHINE LEARNING ALGORITHMS; MODERN MACHINES; NUMBER OF ITERATIONS; SPEED UP;

COLLABORATIVE FILTERING;

EID: 85077475089     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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