Dynamic tuning of the workload partition factor and the resource utilization in data-intensive applications

Author:

Rosas ClaudiaORCID,Sikora Anna,Jorba Josep,Moreno Andreu,Espinosa Antonio,César Eduardo

Funder

MICINN Spain

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference32 articles.

1. Parallel data intensive computing in scientific and commercial applications;Cannataro;Parallel Comput.,2002

2. Data-Intensive Supercomputing: the Case for DISC, Tech. rep.;Bryant,2007

3. R.E. Bryant, R.H. Katz, E.D. Lazowska, Big-data computing, White paper, Computing Research Association, 2008.

4. ScalaBLAST: a scalable implementation of BLAST for high-performance data-intensive bioinformatics analysis;Oehmen;IEEE Trans. Parallel Distrib. Syst.,2006

5. V. Bharadwaj, D. Ghose, T.G. Robertazzi, Divisible load theory: a new paradigm for load scheduling in distributed syestems, in: CLUSTER ’03, Vol. 6, 2003, pp. 7–17.

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