Revisiting Flynn’s Classification: The Portfolio Approach
Conference paper
First Online:
Abstract
Today, we are reaching the limits of Moore’s law: the progress of parallel components does not grow exponentially as it did continuously during the last decades. This is somehow a paradox since the computing platforms are always more powerful. It simply tells us that the efficiency of parallel programs is becoming less obvious.
If we want to continue to solve hard computational problems, the only way is to change the way problems are solved. In this work, we propose to investigate how algorithms portfolio may be a direction to solve hard and large problems. It is also the occasion for us to revisit the well-known Flynn’s classification and clarifying the MISD (Multiple Instructions Single Data) class which was never really well-understood.
Keywords
Flynn’s taxonomy Algorithm portfolio Cooperative parallelismReferences
- 1.Bougeret, M., Dutot, P., Goldman, A., Ngoko, Y., Trystram, D.: Combining multiple heuristics on discrete resources. In: 23rd IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2009, Rome, Italy, 23–29 May 2009, pp. 1–8. IEEE (2009)Google Scholar
- 2.Bougeret, M., Dutot, P., Goldman, A., Ngoko, Y., Trystram, D.: Approximating the discrete resource sharing scheduling problem. Int. J. Found. Comput. Sci. 22(3), 639–656 (2011)MathSciNetCrossRefMATHGoogle Scholar
- 3.Bovet, D., Cesati, M.: Understanding the Linux Kernel. Oreilly & Associates Inc., Sebastopol (2005)Google Scholar
- 4.Darema, F., George, D., Norton, V., Pfister, G.: A single-program-multiple-data computational model for EPEX/FORTRAN. Parallel Comput. 7(1), 11–24 (1988)CrossRefMATHGoogle Scholar
- 5.Diderot, D., le Rond d’Alembert, J., (eds.): Encyclopédie, ou dictionnaire raisonné des sciences, des arts et des métiers. André le Breton, Michel-Antoine David, Laurent Durand and Antoine-Claude Briasson, France (1751–1766)Google Scholar
- 6.Feng, T.Y.: Some characteristics of associative parallel processing. In: Proceedings of the 1972 Sagamore Computing Conference, pp. 5–16 (1972)Google Scholar
- 7.Flynn, M.J.: Some computer organizations and their effectiveness. IEEE Trans. Comput. 21(9), 948–960 (1972)CrossRefMATHGoogle Scholar
- 8.Flynn, M.J., Rudd, K.W.: Parallel architectures. ACM Comput. Surv. 28(1), 67–70 (1996)CrossRefGoogle Scholar
- 9.Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman & Co., New York (1979)MATHGoogle Scholar
- 10.Händler, W.: The impact of classification schemes on computer architecture. In: Agrawal, D.P. (ed.) Advanced Computer Architecture, pp. 3–11. IEEE Computer Society Press, Los Alamitos (1986)Google Scholar
- 11.Huberman, B.A., Lukose, R.M., Hogg, T.: An economics approach to hard computational problems. Science 275(5296), 51–54 (1997)CrossRefGoogle Scholar
- 12.Lameter, C.: Numa (non-uniform memory access): an overview. Queue 11(7), 40:40–40:51 (2013)CrossRefGoogle Scholar
- 13.Null, L., Lobur, J.: Essentials of Computer Organization and Architecture, 3rd edn. Jones and Bartlett Publishers, Inc., USA (2010)Google Scholar
- 14.Streeter, M.J., Golovin, D., Smith, S.F.: Combining multiple heuristics online. In: Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 22–26 July 2007, Vancouver, British Columbia, Canada, pp. 1197–1203 (2007)Google Scholar
- 15.Thurlow, R.: RPC: remote procedure call protocol specification version 2. Technical report, Sun Microsystems (2009)Google Scholar
- 16.Vardi, M.Y.: Moore’s law and the sand-heap paradox. Commun. ACM 57(5), 5 (2014)CrossRefGoogle Scholar
Copyright information
© Springer International Publishing AG, part of Springer Nature 2018