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Abstract

Summary

The cloud computing paradigm is enabling the execution of high performance computing software and is a potential alternative to traditional clusters. Not only that, but public providers, such as Microsoft and Amazon, offer a wide variety of virtual machine specifications and prices. Correctly choosing the proper hardware specification for the software can reduce execution times and money. In light of this, we developed an algorithm that automatically selects the virtual machine configurations with the best cost per performance ratio in the Amazon Web Service cloud platform for a running software, using its performance in differently priced configurations as input to the selection. Our results showed that the algorithm is capable of selecting the instances that offers the best cost per performance within minutes, approaching the optimal cost as the dataset size increases.

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/content/papers/10.3997/2214-4609.201900770
2019-06-03
2024-04-20

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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201900770
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Optimizing the Execution Costs of High-Performance Geophysics Software on the Cloud
Conference Proceedings 2019, 1 (2019); https://doi.org/10.3997/2214-4609.201900770
/content/papers/10.3997/2214-4609.201900770
/content/papers/10.3997/2214-4609.201900770
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