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.
Supported by Petrobras, Fapesp, CNPq, and CAPES.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amazon: Amazon EC2 Reserved Instances pricing. https://aws.amazon.com/ec2/pricing/reserved-instances/pricing/ (2019). Accessed 03 May 2019
Borin, E., Benedicto, C., Rodrigues, I.L., Pisani, F., Tygel, M., Breternitz, M.: PY-PITS: a scalable Python runtime system for the computation of partially idempotent tasks. In: 2016 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW) (2016). https://doi.org/10.1109/SBAC-PADW.2016.10
Fomel, S., Kazinnik, R.: Non-hyperbolic common reflection surface. Geophys. Prospect. 61(1) (2012). https://doi.org/10.1111/j.1365-2478.2012.01055.x
Li, Z., et al.: Spot pricing in the cloud ecosystem: a comparative investigation. J. Syst. Softw. 114, 1–9 (2016). https://doi.org/10.1016/j.jss.2015.10.042
Okita, N., Coimbra, T., Rodamilans, C., Tygel, M., Borin, E.: Using SPITS to optimize the cost of high-performance geophysics processing on the cloud. In: First EAGE Workshop on High Performance Computing for Upstream in Latin America. EAGE Publications BV (2018). https://doi.org/10.3997/2214-4609.201803077
Okita, N., Rodamilans, C., Coimbra, T., Tygel, M., Borin, E.: Otimização automática do custo de processamento de programas SPITS na AWS. In: Anais da Trilha Principal do XIX Simpósio em Sistemas Computacionais de Alto Desempenho (WSCAD 2018), pp. 196–207, SBC (2018)
Shastri, S., Irwin, D.: Hotspot: automated server hopping in cloud spot markets. In: Proceedings of the 2017 Symposium on Cloud Computing. ACM (2017)
Subramanya, S., Guo, T., Sharma, P., Irwin, D., Shenoy, P.: SpotOn: a batch computing service for the spot market. In: Proceedings of the Sixth ACM Symposium on Cloud Computing. ACM (2015)
Wan, J., Gui, X., Zhang, R.: Dynamic bidding in spot market for profit maximization in the public cloud. J. Supercomput. 73(10), 4245–4274 (2017). https://doi.org/10.1007/s11227-017-2007-9
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Okita, N.T., Coimbra, T.A., Rodamilans, C.B., Tygel, M., Borin, E. (2020). Automatic Minimization of Execution Budgets of SPITS Programs in AWS. In: Bianchini, C., Osthoff, C., Souza, P., Ferreira, R. (eds) High Performance Computing Systems. WSCAD 2018. Communications in Computer and Information Science, vol 1171. Springer, Cham. https://doi.org/10.1007/978-3-030-41050-6_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-41050-6_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-41049-0
Online ISBN: 978-3-030-41050-6
eBook Packages: Computer ScienceComputer Science (R0)