Faster and cheaper: How graphics processing units on spot-market instances minimize turnaround time and budget

Author:

Okita Nicholas T.1ORCID,Coimbra Tiago A.1ORCID

Affiliation:

1. University of Campinas, Center for Petroleum Studies, Rua Cora Coralina, 350, Cidade Universitária 13089-970, Campinas, São Paulo, Brazil.(corresponding author); .

Abstract

Cloud computing is enabling users to instantiate and access high-performance computing clusters quickly. However, without proper knowledge of the type of application and the nature of the instances, it can become quite expensive. Our objective is to indicate that adequately choosing the instances provides a fast execution, which, in turn, leads to a low execution price, using the pay-as-you-go model on cloud computing. We have used graphics processing unit instances on the spot market to execute a seismic-data set interpolation job and compared their performance with regular on-demand central processing unit (CPU) instances. Furthermore, we explored how scaling could also improve the execution times at small price differences. The experiments have shown that, by using an instance with eight accelerators on the spot market, we obtain up to a 300 times speed-up compared with the on-demand CPU options, while being 100 times cheaper. Finally, our results have shown that seismic-imaging processing can be sped up by an order of magnitude with a low budget, resulting in faster and cheaper processing turnaround time and enabling new possible imaging techniques.

Publisher

Society of Exploration Geophysicists

Subject

Geology,Geophysics

Reference18 articles.

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2. Amazon, 2017, Amazon Web Services: Risk and compliance whitepaper, http://d0.awsstatic.com/whitepapers/compliance/AWS_Risk_and_Compliance_Whitepaper.pdf, accessed 4 August 2020

3. Sharing Learnings: The Methodology, Optimisation and Benefits of Moving Subsurface Data to the Public Cloud

4. Harvesting the computational power of heterogeneous clusters to accelerate seismic processing

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