Skip to main content
  • 372 Accesses

Abstract

While some industries use High Performance Computing (HPC) to increase profits, other industries require HPC to do business at all. In the oil and gas industries, HPC is used to conduct seismic simulations. In the pharmaceutical industry, HPC is used to discover new drugs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    (Weisbord 2004) p.81 is based on Lewin’s “Humanization of the Taylor System: An Inquiry into the Fundamental Psychology of Work and Vocation” published in 1920.

  2. 2.

    See Sect 1.7

References

  • M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. Katz, A. Konwinski, et al., A view of cloud computing. Commun. ACM. 53(4), 50–58 (2010)

    Article  Google Scholar 

  • K.R. Baker, D. Trietsch, Principles of sequencing and scheduling (Wiley, New Jersey, 2013)

    MATH  Google Scholar 

  • D. Bertsimas, V.F. Farias, N. Trichakis, The price of fairness. Oper. Res. 59(1), 17–31 (2011)

    Article  MathSciNet  Google Scholar 

  • B. Committee, Basel III: A global regulatory framework for more resilient banks and banking systems (Basel Committee on Banking Supervision, Basel, 2010)

    Google Scholar 

  • A. Demirguc-Kunt, E. Detragiache, O. Merrouche, Bank capital: Lessons from the financial crisis. J. Money. Credit. Bank. 45(6), 1147–1164 (2013)

    Article  Google Scholar 

  • P. Glasserman, P. Heidelberger, P. Shahabuddin, Efficient monte carlo methods for value-at-risk, (2010)

    Google Scholar 

  • S. Gleeson, International regulation of banking: Basel II, capital and risk requirements (Oxford University Press Catalogue, Oxford, 2010)

    Google Scholar 

  • H. Hakenes, I. Schnabel, Bank size and risk-taking under Basel II. J. Bank. Financ. 35(6), 1436–1449 (2011)

    Article  Google Scholar 

  • M. Harchol-Balter, Performance modeling and design of computer systems: Queueing theory in action (Cambridge University Press, Cambridge, 2013)

    MATH  Google Scholar 

  • H. Hoogeveen, Multicriteria scheduling. Eur. J. Oper. Res. 167(3), 592–623 (2005)

    Article  MathSciNet  Google Scholar 

  • J. Kay, P. Lauder, A fair share scheduler. Commun. ACM. 31(1), 44–55 (1988)

    Article  Google Scholar 

  • S. D. Kleban, S. H. Clearwater, Fair share on high performance computing systems: What does fair really mean? Paper presented at the Cluster Computing and the Grid, 2003. Proceedings. CCGrid 2003. 3rd IEEE/ACM International Symposium on (2003)

    Google Scholar 

  • S. Marston, Z. Li, S. Bandyopadhyay, J. Zhang, A. Ghalsasi, Cloud computing—The business perspective. Decis. Support. Syst. 51(1), 176–189 (2011)

    Article  Google Scholar 

  • R. G. Parker, Deterministic scheduling theory. (CRC Press, 1996)

    Google Scholar 

  • C. Reyes, K. Walters, W. Yang, Monte carlo within a day. Paper presented at the quantitative analysis in financial markets: Collected papers of the New York university mathematical finance seminar (2001)

    Google Scholar 

  • A. Sedighi, Y. Deng, P. Zhang, Fariness of task scheduling in high performance computing environments. Scalable Computing: Pract. Experience 15(3), 273–285 (2014). https://doi.org/10.12694/scpe.v15i3.1020

    Article  Google Scholar 

  • V. T’kindt, J.-C. Billaut, Multicriteria scheduling: theory, models and algorithms (Springer Science & Business Media, Berlin, Heidelberg, 2006)

    MATH  Google Scholar 

  • D.K. Tarullo, Banking on Basel: The future of international financial regulation (Peterson Institute, Washington, D.C., 2008)

    Google Scholar 

  • F. W. Taylor The principles of scientific management (1911)

    Google Scholar 

  • S. Tezuka, H. Murata, S. Tanaka, S. Yumae, Monte Carlo grid for financial risk management. Futur. Gener. Comput. Syst. 21(5), 811–821 (2005)

    Article  Google Scholar 

  • M.R. Weisbord, Productive workplaces revisited: Dignity, meaning, and community in the 21st century (Wiley, Hoboken, 2004)

    Google Scholar 

  • L.H. White, How did we get into this financial mess? (CATO Institue Briefing Papers, Washington, D.C., 2008)

    Google Scholar 

  • L. H. White, Housing finance and the 2008 financial crisis. CATO Institute (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Sedighi, A., Smith, M. (2019). Introduction. In: Fair Scheduling in High Performance Computing Environments. Springer, Cham. https://doi.org/10.1007/978-3-030-14568-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-14568-2_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14567-5

  • Online ISBN: 978-3-030-14568-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics