E. James and . Thornton, Design of a computer: the CDC 6600, 1970.

M. Dungworth, The Cray 1 computer system, Infotech State of the Art Report on Supercomputers, pp.51-76, 1979.

G. Leslie and . Valiant, A Bridging Model for Parallel Computation

H. Fujii, Y. Yasuda, H. Akashi, Y. Inagami, M. Koga et al., Architecture and performance of the Hitachi SR2201 massively parallel processor system, Proceedings 11th International Parallel Processing Symposium, pp.233-241, 1997.
DOI : 10.1109/IPPS.1997.580901

N. Hirose and M. Fukuda, Numerical Wind Tunnel (NWT) and CFD research at National Aerospace Laboratory, Proceedings High Performance Computing on the Information Superhighway. HPC Asia '97, pp.99-103, 1997.
DOI : 10.1109/HPC.1997.592130

S. Michael, . Warren, K. John, . Salmon, J. Donald et al., Pentium pro inside: I. a treecode at 430 gigaflops on asci red, ii. price/performance of USD50/mflop on loki and hyglac, pp.61-61, 1997.

L. Dagum and R. Menon, OpenMP: an industry standard API for shared-memory programming, IEEE Computational Science and Engineering, vol.5, issue.1, pp.46-55, 1998.
DOI : 10.1109/99.660313

W. Eugene, . Myers, G. Granger, . Sutton, L. Art et al., A whole-genome assembly of Drosophila, Science, vol.287, pp.5461-2196, 2000.

A. Pavel, H. Pevzner, . Tang, S. Michael, and . Waterman, An Eulerian path approach to DNA fragment assembly, Proceedings of the National Academy of Sciences 98, pp.17-9748, 2001.

R. Gagan-agrawal, X. Jin, and . Li, Compiler and Middleware Support for Scalable Data Mining, Proceedings of the 14th International Conference on Languages and Compilers for Parallel Computing, LCPC'01, pp.33-51, 2003.
DOI : 10.1007/3-540-35767-X_3

J. Luiz-andré-barroso, U. Dean, and . Holzle, Web search for a planet: The Google cluster architecture, pp.22-28, 2003.

X. Huang, J. Wang, S. Aluru, S. Yang, and L. Hillier, PCAP: A Whole-Genome Assembly Program, Genome Research, vol.13, issue.9, pp.2164-2170, 2003.
DOI : 10.1101/gr.1390403

URL : http://genome.cshlp.org/content/13/9/2164.full.pdf

R. Numrich, Co-Array Fortran Tutorial, p.3, 2003.

R. Rabenseifner, Hybrid Parallel Programming: Performance Problems and Chances, Proceedings of the 45th CUG Conference, 2003.

M. Chaisson, P. Pevzner, and H. Tang, Fragment assembly with short reads, Bioinformatics, vol.20, issue.13, pp.2067-2074, 2004.
DOI : 10.1093/bioinformatics/bth205

URL : https://academic.oup.com/bioinformatics/article-pdf/20/13/2067/666884/bth205.pdf

N. Drosinos and N. Koziris, Performance comparison of pure MPI vs hybrid MPI-OpenMP parallelization models on SMP clusters, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings., 2004.
DOI : 10.1109/IPDPS.2004.1302919

URL : http://www.cslab.ece.ntua.gr/~nkoziris/papers/ipdps2004.pdf

A. David, K. Bader, and . Madduri, Design and implementation of the HPCS graph analysis benchmark on symmetric multiprocessors, pp.465-476, 2005.

R. H. Castain, T. S. Woodall, D. J. Daniel, J. M. Squyres, B. Barrett et al., The Open Run-Time Environment (OpenRTE): A Transparent Multi-cluster Environment for High-Performance Computing, Proceedings, 12th European PVM/MPI Users' Group Meeting, 2005.
DOI : 10.1007/11557265_31

T. El-ghazawi, W. Carlson, T. Sterling, and K. Yelick, UPC: distributed shared memory programming, 2005.
DOI : 10.1002/0471478369

A. Gara, M. A. Blumrich, D. Chen, G. Chiu, P. Coteus et al., Overview of the Blue Gene/L system architecture, IBM Journal of Research and Development 49, pp.3-195, 2005.
DOI : 10.1147/rd.492.0195

R. Jin, G. Yang, and G. Agrawal, Shared Memory Parallelization of Data Mining Algorithms: Techniques, Programming Interface, and Performance, Knowledge and Data Engineering IEEE Transactions on, vol.171, pp.71-89, 2005.
DOI : 10.1137/1.9781611972726.5

R. Rakotomalala, TANAGRA : un logiciel gratuit pour l'enseignement et la recherche Fr, in: Actes de EGC'2005, RNTI-E-3, pp.697-702, 2005.

R. David and . Bentley, Whole-genome re-sequencing " , in: Current opinion in genetics & development 16, pp.545-552, 2006.

K. Datta, D. Bonachea, and K. Yelick, Titanium Performance and Potential: An NPB Experimental Study, Languages and Compilers for Parallel Computing, pp.200-214, 2006.
DOI : 10.1007/978-3-540-69330-7_14

URL : http://titanium.cs.berkeley.edu/papers/datta-bonachea-yelick-ti_npb.pdf

I. Mierswa, M. Wurst, R. Klinkenberg, M. Scholz, and T. Euler, YALE, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '06, pp.935-940, 2006.
DOI : 10.1145/1150402.1150531

R. Michael, N. Berthold, F. Cebron, T. R. Dill, T. Gabriel et al., KNIME: The Konstanz Information Miner, Studies in Classification, Data Analysis, and Knowledge Organization, pp.978-981, 2007.

. Wu-chun-feng, W. Kirk, and . Cameron, The green500 list: Encouraging sustainable supercomputing, pp.50-55, 2007.

P. Konecny, Introducing the Cray XMT, Proc. Cray User Group meeting, 2007.

E. Achtert, H. Kriegel, and A. Zimek, ELKI: A Software System for Evaluation of Subspace Clustering Algorithms, Scientific and Statistical Database Management, pp.580-585, 2008.
DOI : 10.1007/978-3-540-69497-7_41

URL : http://www.dbs.informatik.uni-muenchen.de/Publikationen/Papers/elkipaper.pdf

J. Kevin, K. Barker, A. Davis, . Hoisie, J. Darren et al., Entering the petaflop era: the architecture and performance of Roadrunner, Proceedings of the 2008 ACM/IEEE conference on Supercomputing, p.1, 2008.

L. Glimcher, R. Jin, and G. Agrawal, Middleware for data mining applications on clusters and grids Parallel Techniques for Information Extraction, Journal of Parallel and Distributed Computing, vol.681, pp.37-53, 2008.
DOI : 10.1016/j.jpdc.2007.06.007

URL : http://www.cs.kent.edu/~jin/Papers/JPDC08.pdf

M. Kulkarni, The Galois System: optimistic parallelization of irregular programs Adviser-Pingali, Keshav, pp.978-978, 2008.

M. Adam, . Phillippy, C. Michael, M. Schatz, and . Pop, Genome assembly forensics: finding the elusive mis-assembly, Genome biology, vol.93, p.1, 2008.

R. Daniel, E. Zerbino, and . Birney, Velvet: algorithms for de novo short read assembly using de Bruijn graphs, Genome research, vol.185, pp.821-829, 2008.

T. Abeel, Y. Van-de-peer, and Y. Saeys, Java-ML: A Machine Learning Library, J. Mach. Learn. Res, vol.10, pp.931-934, 2009.

M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann et al., The WEKA data mining software, ACM SIGKDD Explorations Newsletter, vol.11, issue.1, pp.10-18, 2009.
DOI : 10.1145/1656274.1656278

W. Jiang, V. T. Ravi, and G. Agrawal, Comparing map-reduce and FREERIDE for data-intensive applications, 2009 IEEE International Conference on Cluster Computing and Workshops, pp.1-10, 2009.
DOI : 10.1109/CLUSTR.2009.5289199

M. Kulkarni, M. Burtscher, R. Inkulu, K. Pingali, and C. Casçaval, How Much Parallelism is There in Irregular Applications?, Proceedings of the 14th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP '09, pp.3-14, 2009.
DOI : 10.1145/1504176.1504181

URL : http://iss.ices.utexas.edu/Publications/Papers/ppopp2009.pdf

T. Jared, K. Simpson, . Wong, D. Shaun, J. E. Jackman et al., ABySS: a parallel assembler for short read sequence data, Genome research, vol.196, pp.1117-1123, 2009.

S. Boisvert, F. Laviolette, and J. Corbeil, Ray: Simultaneous Assembly of Reads from a Mix of High-Throughput Sequencing Technologies, Journal of Computational Biology, vol.17, issue.11, pp.1519-1533, 2010.
DOI : 10.1089/cmb.2009.0238

URL : http://europepmc.org/articles/pmc3119603?pdf=render

R. Li, H. Zhu, J. Ruan, W. Qian, X. Fang et al., De novo assembly of human genomes with massively parallel short read sequencing, Genome Research, vol.20, issue.2, pp.265-272, 2010.
DOI : 10.1101/gr.097261.109

URL : http://genome.cshlp.org/content/20/2/265.full.pdf

Y. Low, J. Gonzalez, A. Kyrola, D. Bickson, C. Guestrin et al., GraphLab: A New Parallel Framework for Machine Learning, 2010.

G. Malewicz, M. H. Austern, J. Aart, J. C. Bik, I. Dehnert et al., Pregel: A System for Large-scale Graph Processing, pp.135-146, 2010.

C. Richard, . Murphy, B. Kyle, . Wheeler, W. Brian et al., Introducing the graph 500, Cray User's Group (CUG), 2010.

K. Paszkiewicz, J. David, and . Studholme, De novo assembly of short sequence reads, Briefings in Bioinformatics, vol.16, issue.8, p.20, 2010.
DOI : 10.1089/cmb.2009.0047

URL : https://academic.oup.com/bib/article-pdf/11/5/457/4861134/bbq020.pdf

L. Salmela, Correction of sequencing errors in a mixed set of reads, Bioinformatics, vol.18, issue.5, pp.1284-1290, 2010.
DOI : 10.1101/gr.074492.107

V. Saraswat, G. Almasi, G. Bikshandi, C. Cascaval, D. Cunningham et al., The Asynchronous Partitioned Global Address Space Model, tech. rep

C. Michael, B. Schatz, . Langmead, L. Steven, and . Salzberg, Cloud computing and the DNA data race, Nature biotechnology, vol.287, p.691, 2010.

X. Zhao, E. Lance, R. Palmer, C. Bolanos, D. Mircean et al., EDAR: An Efficient Error Detection and Removal Algorithm for Next Generation Sequencing Data, Journal of Computational Biology, vol.17, issue.11, pp.1549-1560, 2010.
DOI : 10.1089/cmb.2010.0127

A. Ghoting, P. Kambadur, E. Pednault, and R. Kannan, NIMBLE, Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '11, pp.334-342, 2011.
DOI : 10.1145/2020408.2020464

E. André, . Minoche, C. Juliane, H. Dohm, and . Himmelbauer, Evaluation of genomic high-throughput sequencing data generated on Illumina HiSeq and genome analyzer systems, Genome biology, vol.12, pp.11-112, 2011.

W. Zhang, J. Chen, Y. Yang, Y. Tang, J. Shang et al., A Practical Comparison of De Novo Genome Assembly Software Tools for Next-Generation Sequencing Technologies, PLoS ONE, vol.215, issue.3, p.17915, 2011.
DOI : 10.1371/journal.pone.0017915.s003

URL : https://doi.org/10.1371/journal.pone.0017915

S. Boisvert, F. Raymond, É. Godzaridis, F. Laviolette, and J. Corbeil, Ray Meta: scalable de novo metagenome assembly and profiling, Genome Biology, vol.13, issue.12, p.1, 2012.
DOI : 10.1093/nar/gkh021

URL : https://genomebiology.biomedcentral.com/track/pdf/10.1186/gb-2012-13-12-r122?site=genomebiology.biomedcentral.com

M. Dayarathna, C. Houngkaew, and T. Suzumura, Introducing ScaleGraph, Proceedings of the ACM SIGPLAN 2012 X10 Workshop on, X10 '12, pp.1-6, 2012.
DOI : 10.1145/2246056.2246062

E. Joseph, Y. Gonzalez, H. Low, D. Gu, C. Bickson et al., PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs, pp.2012-2014

G. Hager, G. Wellein, S. Full, and -. Tutorial, The practitioner's cookbook for good parallel performance on multi-and manycore systems, 2012.

S. Hong, H. Chafi, E. Sedlar, and K. Olukotun, Green-Marl, ACM SIGARCH Computer Architecture News, vol.40, issue.1, pp.349-362, 2012.
DOI : 10.1145/2189750.2151013

W. Huang, L. Li, J. R. Myers, T. Gabor, and . Marth, ART: a nextgeneration sequencing read simulator, Bioinformatics, vol.284, pp.593-594, 2012.
DOI : 10.1093/bioinformatics/btr708

URL : https://academic.oup.com/bioinformatics/article-pdf/28/4/593/16911715/btr708.pdf

D. Khaldi, P. Jouvelot, C. Ancourt, and F. Irigoin, Task Parallelism and Data Distribution: An Overview of Explicit Parallel Programming Languages, International Workshop on Languages and Compilers for Parallel Computing, pp.174-189, 2012.
DOI : 10.1007/978-3-642-37658-0_12

URL : https://hal.archives-ouvertes.fr/hal-00742536

Y. Low, D. Bickson, J. Gonzalez, C. Guestrin, A. Kyrola et al., Distributed GraphLab, Proceedings of the VLDB Endowment, pp.716-727, 2012.
DOI : 10.14778/2212351.2212354

J. Reinders, An Overview of Programming for Intel Xeon processors and Xeon Phi coprocessors, tech. rep., Intel Corporation, 2012.

J. Demsar and B. Zupan, Orange: Data Mining Fruitful and Fun -A Historical Perspective, pp.55-60, 2013.

B. Dupont-de-dinechin, P. Guironnet-de-massas, G. Lager, C. Leger, B. Orgogozo et al., A Distributed Run-Time Environment for the Kalray MPPA-256 Integrated Manycore Processor, 2013 International Conference on Computational Science, pp.1654-1663, 2013.

B. Elser and A. Montresor, An evaluation study of BigData frameworks for graph processing, 2013 IEEE International Conference on Big Data, pp.60-67, 2013.
DOI : 10.1109/BigData.2013.6691555

T. Hoefler, J. Dinan, D. Buntinas, P. Balaji, B. Barrett et al., MPI + MPI: a new hybrid approach to parallel programming with MPI plus shared memory, Computing, vol.14, issue.1, pp.95-107, 2013.
DOI : 10.1109/MCSE.2010.122

Z. Khayyat, K. Awara, A. Alonazi, H. Jamjoom, D. Williams et al., Mizan, Proceedings of the 8th ACM European Conference on Computer Systems, EuroSys '13, pp.169-182, 2013.
DOI : 10.1145/2465351.2465369

M. Sai-charan-koduru, R. Feng, and . Gupta, Programming large dynamic data structures on a dsm cluster of multicores, 7th International Conference on PGAS Programming Models, p.126, 2013.

B. Leback, D. Miles, and M. Wolfe, Tesla vs Xeon Phi vs Radeon: A Compiler Writer's Perspective, Proc. CUG'13, 2013.

Y. Low, GraphLab: A Distributed Abstraction for Large Scale Machine Learning, 2013.

N. Nagarajan and M. Pop, Sequence assembly demystified, Nature Reviews Genetics, vol.23, issue.3, pp.157-167, 2013.
DOI : 10.1093/bioinformatics/btm451

S. Salihoglu and J. Widom, GPS, Proceedings of the 25th International Conference on Scientific and Statistical Database Management, SSDBM, p.22, 2013.
DOI : 10.1145/2484838.2484843

Y. Tian, A. Balmin, S. Severin-andreas-corsten, J. Tatikonda, and . Mcpherson, From "think like a vertex" to "think like a graph", Proc. of the VLDB Endowment, pp.193-204, 2013.
DOI : 10.14778/2732232.2732238

A. Barnawi, O. Batarfi, R. Elshawi, A. Fayoumi, R. Nouri et al., On Characterizing the Performance of Distributed Graph Computation Platforms, Performance Characterization and Benchmarking. Traditional to Big Data, pp.29-43, 2014.
DOI : 10.1007/978-3-319-15350-6_3

B. Dalton, G. Tanase, M. Alvanos, G. Almasi, and E. Tiotto, Memory Management Techniques for Exploiting RDMA in PGAS Languagues, The 27th International Workshop on Languages and Compilers for Parallel Computing (LCPC), 2014.
DOI : 10.1007/978-3-319-17473-0_13

T. Fleig, O. Mattes, and W. Karl, Evaluation of Adaptive Memory Management Techniques on the Tilera TILE-Gx Platform, Proc. Workshop ARCS'14, 2014.

Y. Guo, M. Biczak, A. Varbanescu, C. Iosup, T. Martella et al., How Well Do Graph-Processing Platforms Perform? An Empirical Performance Evaluation and Analysis, 2014 IEEE 28th International Parallel and Distributed Processing Symposium, pp.395-404, 2014.
DOI : 10.1109/IPDPS.2014.49

URL : http://www.pds.ewi.tudelft.nl/~iosup/perf-eval-graph-proc14ipdps.pdf

M. Han, K. Daudjee, K. Ammar, X. Ozsu, T. Wang et al., An experimental comparison of pregel-like graph processing systems, Proc. of the VLDB Endowment, pp.1047-1058, 2014.
DOI : 10.14778/2732977.2732980

URL : http://www.vldb.org/pvldb/vol7/p1047-han.pdf

M. Lau, China's world-beating supercomputer fails to impress some potential clients" http://www.scmp.com/news/china/article/1543226/chinas-world-beating- supercomputer-fails-impress-some-potential-clients

J. Leskovec and A. Krevl, Stanford Large Network Dataset Collection, 2014.

X. Liao, L. Xiao, C. Yang, and Y. Lu, MilkyWay-2 supercomputer: system and application, Frontiers of Computer Science, vol.9, issue.1, pp.345-356, 2014.
DOI : 10.1186/1471-2105-9-104

A. Lulli, Distributed solutions for large scale graph processing, 2014.

R. Nambiar, M. Poess, A. Dey, P. Cao, T. Magdon-ismail et al., Introducing TPCx-HS: The First Industry Standard for Benchmarking Big Data Systems, Performance Characterization and Benchmarking . Traditional to Big Data, pp.1-12, 2014.
DOI : 10.1007/978-3-319-15350-6_1

O. Serres, A. Kayi, A. Anbar, and T. El-ghazawi, Hardware support for address mapping in PGAS languages, Proceedings of the 11th ACM Conference on Computing Frontiers, CF '14, pp.1-22, 2014.
DOI : 10.1145/2597917.2597945

P. Daniel, P. Siewiorek, and . Koopman, The architecture of supercomputers: Titan, a case study, 2014.

D. Sims, I. Sudbery, E. Nicholas, A. Ilott, C. P. Heger et al., Sequencing depth and coverage: key considerations in genomic analyses, Nature Reviews Genetics, vol.2, issue.2, pp.121-132, 2014.
DOI : 10.7554/eLife.00348

A. Varghese, B. Edwards, G. Mitra, and A. P. , Programming the Adapteva Epiphany 64-Core Network-on-Chip Coprocessor, Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, pp.984-992, 2014.
DOI : 10.1177/1094342015599238

URL : http://arxiv.org/pdf/1410.8772

Y. Zhao, K. Yoshigoe, M. Xie, S. Zhou, R. Seker et al., Evaluation and Analysis of Distributed Graph-Parallel Processing Frameworks, Journal of Cyber Security and Mobility, vol.3, issue.3, pp.289-316, 2014.
DOI : 10.13052/jcsm2245-1439.333

URL : http://riverpublishers.com/journal/journal_articles/RP_Journal_2245-1439_333.pdf

A. Abu-doleh, V. Ümit, and . Çatalyürek, Spaler: Spark and GraphX based de novo genome assembler, 2015 IEEE International Conference on Big Data (Big Data), pp.1013-1018, 2015.
DOI : 10.1109/BigData.2015.7363853

R. Chen, J. Shi, Y. Chen, and H. Chen, PowerLyra, Proceedings of the Tenth European Conference on Computer Systems, EuroSys '15, 2015.
DOI : 10.1109/SC.2005.4

B. D. De-dinechin, Kalray MPPA??: Massively parallel processor array: Revisiting DSP acceleration with the Kalray MPPA Manycore processor, 2015 IEEE Hot Chips 27 Symposium (HCS), pp.2015-2016
DOI : 10.1109/HOTCHIPS.2015.7477332

Y. Gao, W. Zhou, J. Han, D. Meng, Z. Zhang et al., An evaluation and analysis of graph processing frameworks on five key issues, Proceedings of the 12th ACM International Conference on Computing Frontiers, CF '15, pp.2015-2026
DOI : 10.1145/2588555.2610518

P. Leonard, Exploring Graph Colouring Heuristics in GraphLab, 2015.

T. Robert-ryan-mccune, G. Weninger, and . Madey, Thinking like a vertex: a survey of vertex-centric frameworks for large-scale distributed graph processing, ACM Computing Surveys 48, p.25, 2015.

H. Fu, J. Liao, J. Yang, L. Wang, Z. Song et al., The Sunway TaihuLight supercomputer: system and applications, Science China Information Sciences, vol.27, issue.7, pp.72001-1869, 2016.
DOI : 10.1177/1094342012456047

L. Salmela, R. Walve, E. Rivals, and E. Ukkonen, Accurate selfcorrection of errors in long reads using de Bruijn graphs, Bioinformatics, p.321, 2016.
DOI : 10.1093/bioinformatics/btw321

URL : https://hal.archives-ouvertes.fr/lirmm-01385006

R. Xia and A. Kim, MERmaid: A Parallel Genome Assembler for the Cloud