Towards Optimizing Cost and Performance for Parallel Workloads in Cloud Computing

William Maas, Fábio Rossi, Marcelo Luizelli, Philippe Navaux, Arthur Lorenzon

2025

Abstract

The growing popularity of data-intensive applications in cloud computing necessitates a cost-effective approach to harnessing distributed processing capabilities. However, the wide variety of instance types and configurations available can lead to substantial costs if not selected based on the parallel workload requirements, such as CPU and memory usage and thread scalability. This situation underscores the need for scalable and economical infrastructure that effectively balances parallel workloads’ performance and expenses. To tackle this issue, this paper comprehensively analyzes performance, costs, and trade-offs across 18 parallel workloads utilizing 52 high-performance computing (HPC) optimized instances from three leading cloud providers. Our findings reveal that no single instance type can simultaneously offer the best performance and the lowest costs across all workloads. Instances that excel in performance do not always provide the best cost efficiency, while the most affordable options often struggle to deliver adequate performance. Moreover, we demonstrate that by customizing instance selection to meet the specific needs of each workload, users can achieve up to 81.2% higher performance and reduce costs by 95.5% compared to using a single instance type for every workload.

Paper Citation

in Harvard Style

Maas W., Rossi F., Luizelli M., Navaux P. and Lorenzon A. (2025). Towards Optimizing Cost and Performance for Parallel Workloads in Cloud Computing. In Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER; ISBN 978-989-758-747-4, SciTePress, pages 231-238. DOI: 10.5220/0013421600003950

in Bibtex Style

@conference{closer25,
author={William Maas and Fábio Rossi and Marcelo Luizelli and Philippe Navaux and Arthur Lorenzon},
title={Towards Optimizing Cost and Performance for Parallel Workloads in Cloud Computing},
booktitle={Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER},
year={2025},
pages={231-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013421600003950},
isbn={978-989-758-747-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER
TI - Towards Optimizing Cost and Performance for Parallel Workloads in Cloud Computing
SN - 978-989-758-747-4
AU - Maas W.
AU - Rossi F.
AU - Luizelli M.
AU - Navaux P.
AU - Lorenzon A.
PY - 2025
SP - 231
EP - 238
DO - 10.5220/0013421600003950
PB - SciTePress