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Automatic Minimization of Execution Budgets of SPITS Programs in AWS

  • Nicholas T. OkitaEmail author
  • Tiago A. Coimbra
  • Charles B. Rodamilans
  • Martin Tygel
  • Edson Borin
Conference paper
  • 4 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1171)

Abstract

Cloud computing platforms offer a wide variety of computational resources with different performance specifications for different prices. In this work, we experiment how Spot instances and Availability Zones on the Amazon Web Services (AWS) could be utilized to reduce the processing budget. Not only that, but we propose instance selection algorithms in AWS to minimize the execution budget of programs implemented using the programming model Scalable Partially Idempotent Task System (SPITS). Our results show that the proposed method can identify and dynamically adjust the virtual machine types that offer the best price per performance ratio. Therefore, we conclude that our algorithms can minimize the budget given a long enough execution time, except in situations where the startup overhead caused the budget difference or in a short period execution.

Keywords

Cloud-computing Auto-scaling Economics 

Notes

Acknowledgments

This work was possible thanks to the support of Petrobras, CNPq (313012/2017-2), and Fapesp (2013/08293-7). The authors also thank the High-Performance Geophysics (HPG) team for technical support.

References

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Nicholas T. Okita
    • 1
    Email author
  • Tiago A. Coimbra
    • 1
  • Charles B. Rodamilans
    • 1
    • 2
  • Martin Tygel
    • 1
  • Edson Borin
    • 1
    • 3
  1. 1.Center for Petroleum Studies (CEPETRO)University of Campinas (UNICAMP)CampinasBrazil
  2. 2.Computing and Informatics Department (FCI)Mackenzie Presbyterian University (MPU)São PauloBrazil
  3. 3.Institute of Computing (IC)University of Campinas (UNICAMP)CampinasBrazil

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