PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Opportunity Cost Model of the Task Scheduling in Heterogeneous Systems

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Możliwość wykorzystania modelu kosztów w projektowaniu kolejności zadań w systemach niejednorodnych
Języki publikacji
EN
Abstrakty
EN
With the micro-electronics technology has encountered a bottleneck, adding heterogeneous core has become the primary means of increasing processor speed. However, how to assign heterogeneous processor to maximize the performance becomes an urgent problem. The problem has been proved to be NP-complete problem, i.e. it cannot find the optimal solution in polynomial time. This article draws on the idea of the economy, given the concept of opportunity cost in heterogeneous systems, and were analyzed by the opportunity cost model for task scheduling on heterogeneous systems. On this basis, draw the basic principles of a number of task scheduling. Theory and simulation results show that the task assignment algorithm to achieve the desired performance.
PL
Przy projektowaniu układów mikroelektronicznych niejednorodny rdzeń umożliwia zwiększenie szybkości procesora. W artykule przedstawiono ideę uwzględnienia modelu kosztów do projektowania kolejności zadań w systemie niejednorodnym.
Rocznik
Strony
177--180
Opis fizyczny
Bibliogr. 23 poz., tab., wykr.
Twórcy
autor
  • National laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology
autor
  • National laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology
autor
  • National laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology
autor
  • National laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology
Bibliografia
  • [1] Dj.M. Maric, P.F. Meier and S.K. Estreicher: Mater. Sci. Forum Vol. 83-87 (1992), p. 119
  • [2] M.A. Green: High Efficiency Silicon Solar Cells (Trans Tech Publications, Switzerland 1987).
  • [3] Y. Mishing, in: Diffusion Processes in Advanced Technological Materials, edtied by D. Gupta Noyes Publications/William Andrew Publising, Norwich, NY (2004), in press.
  • [4] G. Henkelman, G.Johannesson and H. Jónsson, in: Theoretical Methods in Condencsed Phase Chemistry, edited by S.D. Schwartz, volume 5 of Progress in Theoretical Chemistry and Physics, chapter, 10, Kluwer Academic Publishers (2000).
  • [5] R.J. Ong, J.T. Dawley and P.G. Clem: submitted to Journal of Materials Research (2003)
  • [6] P.G. Clem, M. Rodriguez, J.A. Voigt and C.S. Ashley, U.S. Patent 6,231,666. (2001)
  • [7] Information on http://www.weld.labs.gov.cn
  • [8] Silberschatz A, Galvin P B, Gagne G, et al. Operating system concepts, 4[M]. [S.l.]: Addison-Wesley, 1998.
  • [9] Tanenbaume, S A. Modern operating systems, 2[M]. [S.l.]: Prentice Hall New Jersey, 1992.
  • [10] Lo, M V. Heuristic algorithms for task assignment in distributed systems[J]. Computers, IEEE Transactions on, 1988, 37(11): 1384-1397.
  • [11] Casavant T L, Kuhl J G. A taxonomy of scheduling in generalpurpose distributed computing systems[J]. Software Engineering, IEEE Transactions on, 1988, 14(2): 141-154.
  • [12] Shen C C, Tsai W H. A graph matching approach to optimal task assignment in distributed computing systems using a minimax criterion[J]. Computers, IEEE Transactions on, 1985, 100(3): 197-203.
  • [13] Grimshaw A S, Weissman J B, West E A, et al. Metasystems: an approach combining parallel processing and heterogeneous distributed computing systems[J]. Journal of Parallel and Distributed Computing, 1994, 21(3): 257-270.
  • [14] ChafiI H, Devito Z, Moors A, et al. Language virtualization for heterogeneous parallel computing[Z]. [S.l.]: [s.n.], 2010: 835-847.
  • [15] Buyya R, others. High performance cluster computing: architectures and systems (volume 1)[J]. Prentice Hall, Upper Saddleriver, Nj, USA, 1999, 1(期缺失): 999.
  • [16] Sunderam V S, Geist G A. Heterogeneous parallel and distributed computing[J]. Parallel Computing, 1999, 25(13/14): 1699-1721.
  • [17] Wang L, Siegel H J, Roychowdhury V P, et al. Task matching and scheduling in heterogeneous computing environments using a genetic-algorithm-based approach[J]. Journal of Parallel and Distributed Computing, 1997, 47(1): 8-22.
  • [18] Saha D, Menasce D, Porto S, et al. Static and dynamic processor scheduling disciplines in heterogeneous parallel architectures[J]. Journal of Parallel and Distributed Computing, 1995, 28(1): 1-18.
  • [19] IVerson M A, F O Z, Follen G J. Parallelizing existing applications in a distributed heterogeneous environment[Z]. [S.l.]: [s.n.], 1995.
  • [20] Lastovestky A, Reddy R. On performance analysis of heterogeneous parallel algorithms[J]. Parallel Computing, 2004, 30(11): 1195-1216.
  • [21] Clematis A, Corana A. Modeling performance of heterogeneous parallel computing systems[J]. Parallel Computing, 1999, 25(9): 1131-1145.
  • [22] Case K E, Fair R C. Principles of microeconomics[M]. [S.l.]: Pearson Education, 2007.
  • [23] Mankiw, G N. Principles of economics[M]. [S.l.]: South-Western Pub, 2011.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-47803b2f-3ceb-4490-a9c2-0c86f187261a
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.