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3. McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky,
A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., DePristo, M.A.: The
genome analysis toolkit: a mapreduce framework for analyzing next-generation
dna sequencing data. Genome Res. 20 , 1297-1303 (2010)
4. Starr, D.L., Bloom, J.S., Brewer, J.M., Butler, N., Clein, C.: A map/reduce paral-
lelized framework for rapidly classifying astrophysical transients. In: Astronomical
Data Analysis Software and Systems XIX, Series, vol. 434. ASP Conference Series
(2010)
5. Zaharia, M., Konwinski, A., Joseph, A.D., Katz, R., Stoica, I.: Improving mapre-
duce performance in heterogeneous environments. In: Proceedings of the 8th
USENIX Conference on Operating Systems Design and Implementation, Series,
OSDI 2008, pp. 29-42. USENIX Association, Berkeley (2008). http://dl.acm.org/
citation.cfm?id=1855741.1855744
6. Xie, J., Yin, S., Ruan, X., Ding, Z., Tian, Y., Majors, J., Manzanares, A., Quin,
X.: Improving mapreduce performance through data placement in heterogeneous
hadoop clusters. In: IPDPS Workshops, pp. 1-9 (2010)
7. The FutureGrid Resource Project: An XSEDE Resource Provider. https://portal.
futuregrid.org/about
8. National Energy Research Scientific Computing Center. http://nersc.gov
9. Fadika, Z., Dede, E., Hartog, J., Govindaraju, M.: Marla: mapreduce for hetero-
geneous and load imbalanced clusters. In: 2012 12th IEEE/ACM International
Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 49-56, May
2012
10. Fadika, Z., Dede, E., Govindaraju, M., Ramakrishnan, L.: Benchmarking mapre-
duce implementations for application usage scenarios. In: IEEE/ACM Interna-
tional Workshop on Grid Computing, pp. 90-97 (2011)
11. Ahmad, F., Chakradhar, S.T., Raghunathan, A., Vijaykumar, T.: Tarazu: optimiz-
ing mapreduce on heterogeneous clusters. ACM SIGARCH Comput Archit. News
40 (1), 61-74 (2012)
12. HDFS. http://hadoop.apache.org/docs/hdfs/r0.22.0/hdfs design.html
13. Hartog, J., DelValle, R., Govindaraju, M., Lewis, M.: Configuring a mapreduce
framework for performance-heterogeneous clusters. In: Proceedings of the 2013
IEEE Big Data 2014 Conference, Research Track, Series, BigData 2014, Anchorage,
AL, USA (2014)
14. Nathuji, R., Isci, C., Gorbatov, E.: Exploiting platform heterogeneity for power e-
cient data centers. In: Fourth International Conference on Autonomic Computing,
ICAC 2007, p. 5. IEEE (2007)
15. Fadika, Z., Dede, E., Govindaraju, M., Ramakrishnan, L.: Mariane: mapreduce
implementation adapted for HPC environments. In: IEEE/ACM International
Workshop on Grid Computing, pp. 82-89 (2011)
16. General Parallel File System. http://www-03.ibm.com/systems/software/gpfs
17. Thusoo, A., Sarma, J.S., Jain, N., Shao, Z., Chakka, P., Anthony, S., Liu, H.,
Wyckoff, P., Murthy, R.: Hive: a warehousing solution over a map-reduce frame-
work. Proc. VLDB Endowment 2 (2), 1626-1629 (2009)
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