Robust evaluation of GPU compute instances for HPC and AI in the cloud: a TOPSIS approach with sensitivity, bootstrapping, and non-parametric analysis

IF 3.3 3区计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Computing Pub Date : 2024-09-06 DOI:10.1007/s00607-024-01342-6

Mandeep Kumar, Gagandeep Kaur, Prashant Singh Rana

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Abstract

Evaluating GPU compute instances for High Performance Computing (HPC) and Artificial Intelligence (AI) applications in the cloud involves complex decision-making processes. This research applies the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank various GPU compute instances for HPC and AI from leading cloud providers: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI). The analysis incorporates a sensitivity examination, bootstrapping, and non-parametric tests to ensure robust and reliable rankings. Sensitivity analysis reveals the stability of the TOPSIS framework despite variations in criteria weights, while bootstrap analysis provides confidence intervals for the rankings, highlighting their consistency. The Friedman test confirms that ranking stability persists across different scenarios, indicating minimal impact from weight adjustments. Despite these insights, limitations such as interdependencies among criteria, data accuracy, and generalizability constraints must be acknowledged. This comprehensive approach ensures informed decision-making for selecting optimal GPU instances for cloud-based HPC and AI tasks.

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云计算中用于高性能计算和人工智能的 GPU 计算实例的稳健评估：采用敏感性、引导和非参数分析的 TOPSIS 方法

评估云中高性能计算（HPC）和人工智能（AI）应用的 GPU 计算实例涉及复杂的决策过程。本研究采用 "与理想解决方案相似度排序技术"（TOPSIS），对主要云提供商提供的用于高性能计算和人工智能的各种 GPU 计算实例进行排序：亚马逊网络服务（AWS）、微软 Azure、谷歌云平台（GCP）和甲骨文云基础设施（OCI）。分析结合了灵敏度检查、引导和非参数检验，以确保排名稳健可靠。灵敏度分析揭示了 TOPSIS 框架在标准权重变化的情况下的稳定性，而自举分析提供了排名的置信区间，突出了排名的一致性。弗里德曼检验证实，在不同的情况下，排名的稳定性依然存在，这表明权重调整的影响微乎其微。尽管获得了这些启示，但仍必须承认一些局限性，如标准之间的相互依存性、数据准确性和可推广性限制。这种综合方法可确保为基于云的高性能计算和人工智能任务选择最佳 GPU 实例做出明智的决策。

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来源期刊

Computing 工程技术-计算机：理论方法

CiteScore

8.20

自引率

2.70%

发文量

107

审稿时长

3 months

期刊介绍： Computing publishes original papers, short communications and surveys on all fields of computing. The contributions should be written in English and may be of theoretical or applied nature, the essential criteria are computational relevance and systematic foundation of results.