The Journal of Supercomputing

, Volume 71, Issue 12, pp 4476–4503 | Cite as

Historical review and future challenges in Supercomputing and Networks of Scientific Communication

  • Álvaro Fernández-González
  • Rafael Rosillo
  • José Ángel Miguel-Dávila
  • Vicente Matellán
Article

Abstract

Supercomputing involves not only the development and provision of infrastructures of large capacity for the scientific and business community, but a new way to manage the tasks of research, development and innovation, making it necessary to use high-capacity communication networks that allow the transfer of a great volume of data between research and high-performance computing facilities. When first implemented, the use of supercomputers occurred mainly in the military field, at which point they were very rudimentary, offering little possibility of communication networking. Over the years, the improvement of security, privacy and service quality in information exchange has facilitated the creation of large networks for scientific communication, which in turn have allowed the incorporation of infrastructures for high-performance computing into the improvement of science. This paper analyzes the evolution of Supercomputing and Scientific Communications Networks by means of a critical review of its present state, as well as identifies the main uses today and predicts the challenges of the future uses of this type of advanced services.

Keywords

Supercomputing Simulations Network of Scientific Communication Scientific collaboration Energy consumption 

References

  1. 1.
    Akhgar B, Saathoff GB, Arabnia HR, Hill R, Staniforth A, Bayerl PS (2015) Application of big data for national security: a practitioner’s guide to emerging technologies. Butterworth-Heinemann Elsevier Ltd, Oxford, United KingdomGoogle Scholar
  2. 2.
    Alonso-Pérez S, Cuevas E, Pérez C, Querol X, Baldasano JM, Draxler R, De Bustos JJ (2011) Trend changes of African airmass intrusions in the marine boundary layer over the subtropical Eastern North Atlantic region in winter. Tellus Ser B-Chem Phys Meteorol 63(2):255–265CrossRefGoogle Scholar
  3. 3.
    Arabnia HR (1990) A parallel algorithm for the arbitrary rotation of digitized images using process-and-data-decomposition approach. J Parallel Distrib Comput 10(2):188–193CrossRefGoogle Scholar
  4. 4.
    Arabnia HR (1995) A distributed stereocorrelation algorithm. In: Proceedings of computer communications and networks (ICCCN’95) Fourth International Conference. IEEE, pp 479–482. doi:10.1109/ICCCN.1995.540163
  5. 5.
    Arabnia HR, Bhandarkar SM (1996) Parallel stereocorrelation on a reconfigurable multi-ring network. J Supercomput 10(3):243–270 (Springer Publishers)MATHCrossRefGoogle Scholar
  6. 6.
    Arabnia HR, Oliver MA (1987) A transputer network for the arbitrary rotation of digitised images. Comput J 30(5):425–433CrossRefGoogle Scholar
  7. 7.
    Arabnia HR, Oliver MA (1987) Arbitrary rotation of raster images with SIMD machine architectures. Comput Graph Forum 6(1):3–11. doi:10.1111/j.1467-8659.1987.tb00340.x CrossRefGoogle Scholar
  8. 8.
    Arabnia HR, Oliver MA (1989) A transputer network for fast operations on digitised images. Comput Graph Forum 8(1):3–11. doi:10.1111/j.1467-8659.1989.tb00448.x CrossRefGoogle Scholar
  9. 9.
    Arabnia HR, Smith JW (1993) A reconfigurable interconnection network for imaging operations and its implementation using a multi-stage switching box. In: Proceedings of the 7th annual international high performance computing conference. The 1993 high performance computing: new horizons supercomputing symposium, Calgary, Alberta, Canada pp 349–357Google Scholar
  10. 10.
    Arif WM, Arabnia HR (2003) Parallel edge-region-based segmentation algorithm targeted at reconfigurable multi-ring network. J Supercomput 25(1):43–63MATHCrossRefGoogle Scholar
  11. 11.
    Asif M, Cencerrado A, Mula-Valls O, Manubens D, Doblas-Reyes F, Cortés A (2014) Impact of I/O and data management in ensemble large scale climate forecasting using Ec-Earth3. Procedia Comput Sci 29:2370–2379. doi:10.1016/j.procs.2014.05.221
  12. 12.
    Aspray W, Williams BO (1994) Arming American scientists: NSF and the provision of scientific computing facilities for universities, 1950–1973. Ann Hist Comput IEEE 16(4):60–74CrossRefGoogle Scholar
  13. 13.
    Atkins D (2003) Report of the National Science Foundation Blue-Ribbon Advisory Panel on Cyberinfrastructure. National Science FoundationGoogle Scholar
  14. 14.
    Atkins D, Borgman C, Bindoff N, Ellisman M, Feldman S, Foster I,Ynnerman A (2010) Building a UK foundation for the transformative enhancement of research and innovation. Report of the international panel for the 2009 review of the UK research councils e-scienceprogramme, SwindonGoogle Scholar
  15. 15.
    Attig N, Gibbon P, Lippert T (2011) Trends in supercomputing: the European path to exascale. Comput Phys Commun 182(9):2041–2046CrossRefGoogle Scholar
  16. 16.
    Aulkner L (2006) Internet 2 about us. http://www.internet2.edu/about. Accessed 12 Nov 2014
  17. 17.
    Avila M, Folch A, Houzeaux G, Eguzkitza B, Prieto L, Cabezón D (2013) A parallel CFD model for wind farms. Procedia Comput Sci 18:2157–2166CrossRefGoogle Scholar
  18. 18.
    Bacon J (1998) Concurrent system. Operating systems, database and distributed systems: an integrated approach, 3rd edn. Addison WesleyGoogle Scholar
  19. 19.
    Balladini J, Grosclaude E, Hanzich M, Suppi R, Rexachs del Rosario D, Luque Fadón E (2010) Incidence of parallel models and scaling CPU frequency in the energy consumption of the HPC systems programming. In: XVI Congreso Argentino de Ciencias de la Computación (CACIC’10)Google Scholar
  20. 20.
    Banerjee P (1994) Parallel algorithms for VLSI computer-aided design. Prentice-Hall, Inc., Upper Saddle River, NJ, USAGoogle Scholar
  21. 21.
    Bermeo HP, De los Reyes E, Bonavia T (2008) Dimensions of the scientific collaboration and its contribution to the academic research groups’ scientific quality. Res Eval 18(4):301–311Google Scholar
  22. 22.
    Bernhard A (2009) A knowledge-based society needs quality in higher education. Probl Educ 21st Century 12:15–21Google Scholar
  23. 23.
    Bethel EW, Van Rosendale J, Southard D, Gaither K, Childs H, Brugger E, Ahern S (2011) Visualization at supercomputing centers: the tale of little big iron and the three skinny guys. IEEE Comput Graph 31(1):90–95CrossRefGoogle Scholar
  24. 24.
    Bhandarkar SM, Arabnia HR (1995) The REFINE multiprocessor: theoretical properties and algorithms. Parallel Comput 21(11):1783–1806. doi:10.1016/0167-8191(95)00032-9 CrossRefGoogle Scholar
  25. 25.
    Bhandarkar SM, Arabnia HR (1995) The Hough transform on a reconfigurable multi-ring network. J Parallel Distrib Comput 24(1):107–114CrossRefGoogle Scholar
  26. 26.
    Bhandarkar SM, Arabnia HR, Smith JW (1995) A reconfigurable architecture for image processing and computer vision. Int J Pattern Recognit Artif Intell (IJPRAI) 9(2):201–229 (Special issue on VLSI algorithms and architectures for computer vision, image processing, pattern recognition and AI). doi:10.1142/S0218001495000110
  27. 27.
    Biswas R, Dunbar J, Hardman J, Bailey FR, Wheeler L, Rogers S (2012) The impact of high-end computing on NASA missions. IT Prof 14(2):20–28CrossRefGoogle Scholar
  28. 28.
    Bollen J, Fox G, Singhal P (2011) How and where the teragrid supercomputing infrastructure benefits science. J Informetr 5(1):114–121CrossRefGoogle Scholar
  29. 29.
    Brown JR, Dinu V (2013) High performance computing methods for the integration and analysis of biomedical data using SAS. Comput Methods Progr Biomed 112(3):553–562CrossRefGoogle Scholar
  30. 30.
    Bub FL, Mask AC, Wood KR, Krynen DG, Lunde BN, DeHaan CJ, Wallmark JA (2014) The Navy’s application of ocean forecasting to decision support. Oceanography 27(3):126–137CrossRefGoogle Scholar
  31. 31.
    Catlett C, Allcock WE, Andrews P, Aydt RA, Bair R, Balac N, Marsteller J (2006) TeraGrid: analysis of organization, system architecture, and middleware enabling new types of applications. High perfomance computing and grids in action, vol 16, IOS Press, pp 225–249Google Scholar
  32. 32.
    CERN-European Organization for Nuclear Research (2011) Web. http://public.web.cern.ch/public/. Accessed July 2011
  33. 33.
    Comunidad Europea (2010) Assessing Europe’s university-based reseachGoogle Scholar
  34. 34.
    Cosnard M, Trystran D (1995) Parallel algorithms and architectures. International Thomson Computer, BostonGoogle Scholar
  35. 35.
    Davis NE, Robey W, Ferenbaugh CR, Nicholaeff D, Trujillo DP (2012) Paradigmatic shifts for exascale supercomputing. J Supercomput 62(2):1023–1044CrossRefGoogle Scholar
  36. 36.
    De Filippo D, Morillo F, Fernández MT (2008) Indicadores de colaboración científica del CSIC con Latinoamérica en base de datos internacionales. [Indicators of Scientific Collaboration between CSIC and Latin America in International Databases]. Rev Esp de Doc Cient 31(1):66–84CrossRefGoogle Scholar
  37. 37.
    Dongarra JJ, Bunch JR, Moler CB, Stewart GW (1979) LINPACK users’ guide, SIAM. doi:10.1137/1.9781611971811
  38. 38.
    Dongarra JJ, Foster I, Fox G, Gropp W (2002) The sourcebook of parallel computing. Morgan Kaufmann, San Francisco, USAGoogle Scholar
  39. 39.
    Dongarra JJ, Van Der Steen AJ (2012) High-performance computing systems: status and outlook. Acta Numér 21:379–474MATHCrossRefGoogle Scholar
  40. 40.
    Ellingson SR, Smith JC, Baudry J (2014) Polypharmacology and supercomputer-based docking: opportunities and challenges. Mol Simul 40(1):10–11Google Scholar
  41. 41.
    Elmagarmid AK, Samuel A, Ouzzani M (2008) Community-cyberinfrastructure-enabled discovery in science and engineering. IEEE Comput Sci Eng 10(5):46–53CrossRefGoogle Scholar
  42. 42.
    Emmot S, Rison S (2005) Towards 2020 science report. Microsoft ResearchGoogle Scholar
  43. 43.
    Featherstone NA, Browning MK, Brun AS, Toomre J (2009) Effects of fossil magnetic fields on convective core dynamos in a-type stars. Astrophysi J 705(1):1000CrossRefGoogle Scholar
  44. 44.
    Fernbach S (1984) Supercomputers—past, present, prospects. Future Gener Comput Syst 1(1):23–30CrossRefGoogle Scholar
  45. 45.
    Foster I, Kesselman C, Tuecke S (2001) The anatomy of the grid: enabling scalable virtual organizations. Int J High Perform Comput Appl 15(3):200–222CrossRefGoogle Scholar
  46. 46.
    Gaudiani A (2012) Análisis del rendimiento de algoritmos paralelos de propósito general en GPGPU [Performance analysis of parallel algorithms for general purposes in GPGPU]. Doctoral dissertation, Facultad de Informática. http://sedici.unlp.edu.ar/bitstream/handle/10915/22691/Documento_completo__.pdf?sequence=1. Retrieved 10 Aug 2014
  47. 47.
    Geller T (2011) Supercomputing’s exaflop target. Commun ACM 54(8):16–18CrossRefGoogle Scholar
  48. 48.
    Gengler M, Ubeda S, Desprez F (1996) Initiation au parallélisme: concepts, architectures et algorithmes [Introduction to parallelism: concepts, architectures and algorithms]. Masson. ISBN 2-225-85014-3Google Scholar
  49. 49.
    Goldberg D (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USAMATHGoogle Scholar
  50. 50.
    Guellec D, Van Pottelsberghe de la Potterie B (2001) R&D and productivity growth: panel data analysis of 16 OECD countries. OECD Economic Studies No. 33/2, OECD, ParisGoogle Scholar
  51. 51.
    Guevara M, Martínez F, Arevalo G, Gassó S, Baldasano J (2013) An improved system for modelling spanish emissions: HERMESv2.0. Atmos Environ 81:209–222CrossRefGoogle Scholar
  52. 52.
    Hassan AH, Fluke CJ, Barnes DG (2011) Unleashing the power of distributed CPU/GPU architectures: massive astronomical data analysis and visualization case study. arXiv:1111.6661
  53. 53.
    Hauben M (2010) History of ARPANET. http://pages.infinit.net/jbcoco/Arpa-Arpanet-Internet.pdf. Retrieved 23 Oct 2014
  54. 54.
    Hermes H (1969) Enumerability. Decidability. Computability. DieGrundlehren der Mathematischen Wissenschaften in Eeinzedartellungen.Band, vol 127. Springer, BerlinCrossRefGoogle Scholar
  55. 55.
    High Performace Computing Act of 1991 (HPCA) (1991) Act of congress promulgated in the 102nd United States Congress as (Pub.L. 102–194)Google Scholar
  56. 56.
    Hwang K (1993) Advanced computer architecture: parallelism, scalability, programmability. McGraw-Hill, USAGoogle Scholar
  57. 57.
    IDC (2004) White paper: council on competiveness study of US industrial HPC users. http://www.compete.org/storage/images/uploads/File/PDF%20Files/HPC_Users_Survey%202004.pdf. Retrieved 15 June 2014
  58. 58.
    Kantardjiev AA (2012) Quantum.Ligand.Dock: protein-ligand docking with quantum entanglement refinement on a GPU system. Nucl Acids Res 40(W1):W415–W422CrossRefGoogle Scholar
  59. 59.
    Kennedy K, Joy W (1998) Interim report to the president, President’s Information Technology Advisory Committee (PITAC). National Coordination Office for Computing, Information and Communication, 4201 Wilson Blvd, Suite 690, Arlington, VA 22230Google Scholar
  60. 60.
    Kinter JL, Cash B, Achuthavarier D, Adams J, Alshuler E, Dirmeyer P, Wong K et al (2013) Revolutionizing climate modeling with project Athena. A multi-institutional, international collaboration. Bull Am Meteorol Soc 94(2):231–245CrossRefGoogle Scholar
  61. 61.
    Kramer D (2011) Supercomputing has a future in clean energy. Phys Today 64(7):27–29CrossRefGoogle Scholar
  62. 62.
    Kupczyk M, Meyer N (2010) PRACE world-class computational facilities ready for polish scientific community. Comput Methods Sci Technol 2010:57–62CrossRefGoogle Scholar
  63. 63.
    Kwon HI, Kim S, Lee H, Ryu M, Kim T, Choi S (2013) Development of an engineering education framework for aerodynamic shape optimization. Int J Aeronaut Space Sci 14(4):297–309Google Scholar
  64. 64.
    Lavington SH (1978) The Manchester Mark I and atlas: a historical perspective. Commun ACM 21(1):4–12CrossRefGoogle Scholar
  65. 65.
    Lawson SJ, Woodgate M, Steijl R, Barakos GN (2012) High performance computing for challenging problems in computational fluid dynamics. Prog Aeroesp Sci 52:19–29CrossRefGoogle Scholar
  66. 66.
    Lederman D, Maloney W (2003) R&D and development. World Bank Policy Research Working Paper 3024Google Scholar
  67. 67.
    Lee E, Huang H, Dennis JM, Chen P, Wang L (2013) An optimized parallel LSQR algorithm for seismic tomography. Comput Geosci 61:184–197CrossRefGoogle Scholar
  68. 68.
    Leiner BM, Cerf VG, Clark DD, Kahn RE, Kleinrock L, Lynch DC, Wolff S (2009) A brief history of the internet. ACM SIGCOMM Comput Commun Rev 39(5):22–31CrossRefGoogle Scholar
  69. 69.
    Lepora NF, Overton PG, Gurney K (2012) Efficient fitting of conductance-based model neurons from somatic current clamp. J Comput Neurosci 32(1):1–24MathSciNetCrossRefGoogle Scholar
  70. 70.
    Lingerfelt EJ, Messer OE, Desai SS, Holt CA, Lentz EJ (2014) Near real-time data analysis of core-collapse supernova simulations with bellerophon. Procedia Comput Sci 29:1504–1514CrossRefGoogle Scholar
  71. 71.
    Markram H, Meier K, Lippert T, Grillner S, Frackowiak R, Dehaene S, Saria A (2011) Introducing the human brain project. Procedia Comput Sci 7:39–42CrossRefGoogle Scholar
  72. 72.
    Martin HSC, Jha S, Coveney PV (2014) Comparative analysis of nucleotide translocation through protein nanopores using steered molecular dynamics and an adaptive biasing force. J Comput Chem 35(9):692–702CrossRefGoogle Scholar
  73. 73.
    Matsuzaki Y, Uchikoga N, Ohue M, Shimoda T, Sato T, Ishida T, Akiyama Y (2013) MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments. Source Code Biol Med 8:18CrossRefGoogle Scholar
  74. 74.
    Mc. Cartney S (1999) ENIAC: the triumphs and tragedies of the world’s first computer. Walker & Company. ISBN: 0802713483Google Scholar
  75. 75.
    Meuer HW, Gietl H (2013) Supercomputers-prestige objects or crucial tools for science and industry? PIK-Praxis der Informationsverarbeitung und Kommunikation 36(2):117–128CrossRefGoogle Scholar
  76. 76.
    Menhorn F, Reumann M (2013) Genome assembly framework on massively parallel, distributed memory supercomputers. Biomed Eng/Biomed Tech. doi:10.1515/bmt-2013-4309
  77. 77.
    Metcalfe TS, Mathur S, Dogan G, Woitaszek M (2012) First results from the asteroseismic modeling portal. Prog Sol/Stellar Phys Helio- Asteroseismol 462:213Google Scholar
  78. 78.
    Milone D, Azar A, Rufiner L (2002) Supercomputadoras basadas en “clusters” de PCs. Trabajo de desarrollo tecnológico realizado en el Laboratorio de Cibernética de la Facultad de Ingeniería (UNER) [“Supercomputers based on PC “clusters.” Technological development project carried out in the cybernetic laboratory of the engineering faculty]. Revista Ciencia, Docencia y Tecnología 8(25):173–208Google Scholar
  79. 79.
    Moraleda A (2007) Supercomputing: a qualitative leap for competitiveness. Economistas 26(116):294–297Google Scholar
  80. 80.
    Munetomo M (2011) Realizing robust and scalable evolutionary algorithms toward exascale era. In: IEEE congress on evolutionary computation (CEC), pp 312–317Google Scholar
  81. 81.
    National Academy of Sciences (2005) Getting up to speed the future of the future of supercomputing. In: Committee on the future of supercomputing computer science and telecommunications board division on engineering and physical sciences. National Research Council of the National Academies. The National Academies Press. Washington, D.CGoogle Scholar
  82. 82.
    Neic A, Liebmann M, Hoetzl E, Mitchell L, Vigmond EJ, Haase G, Plank G (2012) Accelerating cardiac biodomain simulations using graphics processing units. IEEE Trans Biomed Eng 59(8):2281–2290CrossRefGoogle Scholar
  83. 83.
    Nesmachnow S (2014) Planificación de tareas en sistemas cluster, grid y cloud utilizando algoritmos evolutivos. [Scheduling in cluster systems, grids and clouds using evolutionary algorithms]. Komputer Sapiens 6 (1)Google Scholar
  84. 84.
    Nicolosi F, Della Vecchia P, Ciliberti D (2013) An investigation on vertical tail plane contribution to aircraft sideforce. Aerosp Sci Technol 28(1):401–416CrossRefGoogle Scholar
  85. 85.
    O’Neill JE (1995) The role of ARPA in the development of the ARPANET, 1961–1972. Ann Hist Comput IEEE 17(4):76–81MathSciNetCrossRefGoogle Scholar
  86. 86.
    Patterson CA, Snir M, Graham SL (2005) Getting up to speed: the future of supercomputing. National Academies Press, Washington, D.CGoogle Scholar
  87. 87.
    Perine K (2000) The early adopter—Al Gore and the internet—government activity. The Industry StandardGoogle Scholar
  88. 88.
    Puckelwartz MJ, Pesce L, Nelakuditi V, Dellefave-Castillo L, Golbus JR, Day SM, McNally EM (2014) Supercomputing for the parallelization of whole genome analysis. Bioinformatics 30(11):1508–1513CrossRefGoogle Scholar
  89. 89.
    RedCLARA (2011) Compendio RedCLARA de Redes Nacionales de Investigación y Educación Latinoamericanas. [CLARA compendium of Latin American national research networks and education]. http://dspace.redclara.net/bitstream/10786/918/1/2011_CompendioRedCLARA_ES.pdf. Retrieved 10 June 2014
  90. 90.
    Reumann M, Makalic E, Goudey BW, Inouye M, Bickerstaffe A, Bui M, Hopper JL (2012) Supercomputing enabling exhaustive statistical analysis of genome wide association study data: preliminary results. In: Engineering in medicine and biology society (EMBC), 2012 annual international conference of the IEEE, pp 1258–1261Google Scholar
  91. 91.
    Romer P (1990) Endogenous technological change. J Polit Econ 98(5):71–102CrossRefGoogle Scholar
  92. 92.
    Rosenberg LC (1991) Update on national science foundation funding of the “collaboratory”. Commun ACM 34(12):83CrossRefGoogle Scholar
  93. 93.
    Saini S, Rappleye J, Chang J, Barker D, Mehrotra P, Biswas R (2012) I/O performance characterization of lustre and NASA applications on pleiades. In: 19th international conference on high performance computing. IEEE High Performance Computing (HiPC), pp 1–10Google Scholar
  94. 94.
    Sanz MA (1998) Fundamentos históricos de la Internet en Europa y en España. [Historical foundations of the internet in Europe and Spain]. Boletín Rediris 45. http://www.rediris.es/difusion/publicaciones/boletin/45/enfoque2.html. Retrieved 12 May 2014
  95. 95.
    Saunders VR, Guest MF (1982) Applications of the CRAY-1 for quantum chemistry calculations. Comput Phys Commun 26(3):389–395CrossRefGoogle Scholar
  96. 96.
    Sawyer M, Parsons M (2011) A strategy for research and innovation through high performance computing. The University of Edinburgh, EdinburghGoogle Scholar
  97. 97.
    Schaller R (1997) Moore’s law: past, present and future. Spectrum IEEE 34(6):52–59CrossRefGoogle Scholar
  98. 98.
    Shen B, Nelson B, Cheung S, Tao WK (2013) Improving NASA’s multiscale modeling framework for tropical cyclone climate study. Comput Sci Eng 15(5):56–67CrossRefGoogle Scholar
  99. 99.
    Simmons ML, Wasserman HJ (1990) Performance comparison of the CRAY-2 and CRAY X-MP/416 supercomputers. J Supercomput 4(2):153–167CrossRefGoogle Scholar
  100. 100.
    Singh S (2000) The code book: the secret history of codes and code-breaking: 77–85. Fourth Estate, LondonGoogle Scholar
  101. 101.
    Skupin A, Biberstine J, Boerner K (2013) Visualizing the topical structure of the medical sciences: a self-organizing map approach. Plos One 8(3):e58779. doi:10.1371/journal.pone.0058779
  102. 102.
    Soete L, O’Doherty D, Arnold E, Bounfour A, Fagerberg J, FarinelloU, Schiestock G (2002) Benchmarking national research policies: the impact of RTD on competitiveness and employment (IRCE). AStrata-ETAN Expert Working Group, European Commission DG Research, BrusselsGoogle Scholar
  103. 103.
    Stamatakis A, Aberer AJ, Goll C, Smith SA, Berger SA, Izquierdo-Carrasco F (2012) RAxML-light: a tool for computing terabyte phylogenies. Bioinformatics 28(15):2064–2066CrossRefGoogle Scholar
  104. 104.
    Stein RF, Lagerfjärd A, Nordlund Å, Georgobiani D (2012) Helioseismic data from emerging flux simulations. Prog Sol/Stellar Phys Helio-Asteroseismol 462:345Google Scholar
  105. 105.
    Stone H (1993) High performance computer architectures. Addison Wesley, Massachusetts, USAGoogle Scholar
  106. 106.
    Stoyanov D, Grigorov I, Deleva, A, Kolev N, Peshev Z, Kolarov G, Ivanov D (2013) Remote monitoring of aerosol layers over sofia during sahara dust transport episode (April, 2012). In: Seventeenth international school on quantum electronics: laser physics and applications, pp 87700Y–87700Y. International society for optics and photonics. doi:10.1117/12.2014154
  107. 107.
    Sumiyoshi K (2011) A numerical challenge on the core-collapse supernovae: physics of neutrino and matter at extreme conditions. J Phys Conf Ser 302(1):012060Google Scholar
  108. 108.
    Thornton JE (1970) Design of a computer—the control data 6600, Scott Foresman & Co., Glenview, Illinois, USAGoogle Scholar
  109. 109.
    Toomre J, Augustson KC, Brown BP, Browning MK, Brun AS, Featherstone NA, Miesch MS (2012) New era in 3-D modeling of convection and magnetic dynamos in stellar envelopes and cores. In: Progress in solar/stellar physics with Helio- and asteroseismology, vol 462, pp 331Google Scholar
  110. 110.
    Turpin T, Lian Y, Tong J, Fang X (1995) Technology and innovation networks in the People’s Republic of China. J Ind Stud 2(2):63–74CrossRefGoogle Scholar
  111. 111.
    Um J, Choi H, Song SK, Choi SP, Mook Yoon H, Jung H, Kim TH (2013) Development of a virtualized supercomputing environment for genomic analysis. J Supercomput 65(1):71–85CrossRefGoogle Scholar
  112. 112.
    Utreras F (2014) Visión y Proyectos: el presente y el futuro. [Vision and projects: present and future]. XI Encuentro Temático Nacional Renata—RUP. RedClara, Popayán ColombiaGoogle Scholar
  113. 113.
    Villarubia C (2012) La Comisión Europea dobla el presupuesto para HPC [The European commission doubles the budget for HPC]. http://www.bsc.es/sites/default/files/public/about/news/hpc-22022012-datacenterdynamics.pdf. Retrieved 27 Aug 2014
  114. 114.
    Von Neumann J (1945) First draft of a report on the EDVA. Between the United States Army Ordinance Department and the University of Pennsylvania Moore School of Electrical Engineering University of Pennsylvania. Contract No. W-670-ORD-4926Google Scholar
  115. 115.
    Wang R, Harris C (2013) Scaling radio astronomy signal correlation on heterogeneous supercomputers using various data distribution methodologies. Exp Astron 36(3):433–449CrossRefGoogle Scholar
  116. 116.
    Westerlund S, Harris C (2014) A framework for HI spectral source finding using distributed-memory supercomputing. Publ Astron Soc Aust 31:e023. doi:10.1017/pasa.2014.18 CrossRefGoogle Scholar
  117. 117.
    Wilkes MV, Renwick W (1950) The EDSAC (electronic delay storage automatic calculator). Math Comput 4(30):61–65MathSciNetCrossRefGoogle Scholar
  118. 118.
    Winkel M, Speck R, Huebner H, Arnols L, Krause R, Gibbon P (2012) A massively parallel, multi-disciplinary Barnes–Hut tree code for extreme-scale \(n\)-body simulations. Comput Phys Commun 183(4):880–889Google Scholar
  119. 119.
    Woolgar L (2007) New institutional policies for university-industry links. Jpn Res Policy 36:1261–1274CrossRefGoogle Scholar
  120. 120.
    Wu W (2007) Cultivating research universities and industrial linkages in China: the case of Shanghai. World Dev 35(6):1075–1093CrossRefGoogle Scholar
  121. 121.
    Wu Y, Cai X-C (2014) A fully implicit domain decomposition based ale framework for three-dimensional fluid-structure interaction with application in blood flow computation. J Comput Phys 258:524–537MathSciNetCrossRefGoogle Scholar
  122. 122.
    Yamamoto K (2004) Corporatization of national universities in Japan: revolution for governance or rhetoric for downsizing? Financ Account Manag 20(2):153–181CrossRefGoogle Scholar
  123. 123.
    Yang W, Yoshigoe K, Qin X, Liu JS, Yang JY, Niemierko A, Deng Y, Liu Y, Dunker AK, Chen Z, Wang L, Xu D, Arabnia HR, Tong W, Yang MQ (2014) Identification of genes and pathways involved in kidney renal clear cell carcinoma. BMC Bioinform 15(Suppl 17):S2CrossRefGoogle Scholar
  124. 124.
    Yin S, Luo H, Ding S (2013) Real-time implementation of fault-tolerant control systems with performance optimization. IEEE Trans Ind Electron 61(5):2402–2411CrossRefGoogle Scholar
  125. 125.
    Yoshida H (2013) Cloud-super-computing virtual colonoscopy with motion-based navigation for colon cancer screening. In: IEEE third international conference on ConsumerGoogle Scholar
  126. 126.
    Zhou P, Leydesdorff L (2006) The emergence of China as a leading nation in science. Res Policy 35(1):83–104CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Álvaro Fernández-González
    • 1
  • Rafael Rosillo
    • 1
  • José Ángel Miguel-Dávila
    • 1
  • Vicente Matellán
    • 2
  1. 1.Faculty of Economics and Business Sciences, Fundación Centro de Supercomputación de Castilla y LeónUniversity of LeónLeónSpain
  2. 2.Computer Science FacultyUniversity of LeónLeónSpain

Personalised recommendations