Evaluating HPC-Style CPU Performance and Cost in Virtualized Cloud Infrastructures

📅 2025-03-22
🏛️ SoutheastCon
📈 Citations: 0
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🤖 AI Summary
This study systematically evaluates CPU performance and cost-effectiveness of running HPC-style OpenMP workloads in virtualized environments across major cloud platforms—AWS, Azure, GCP, and OCI. Using the SPEC ACCEL benchmark suite, we conduct a cross-platform, multi-architecture analysis spanning Intel, AMD, and ARM processors, under both on-demand and one-year reserved pricing models. Our methodology integrates rigorous performance measurement with detailed TCO modeling to enable joint performance–cost assessment. Results reveal substantial inter-cloud variation in architectural offerings and pricing strategies; workload characteristics—not vendor branding—should drive instance selection. AWS delivers the highest absolute performance (especially on ARM), but at the highest cost per unit performance. OCI achieves the best overall cost–performance ratio. GCP shows marked performance gains on AMD instances but suffers from poor ARM performance and low cost-efficiency. This work provides an evidence-based, quantitative decision framework for HPC resource provisioning in cloud environments.

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📝 Abstract
This paper evaluates HPC-style CPU performance and cost in virtualized cloud infrastructures using a subset of OpenMP workloads in the SPEC ACCEL suite. Four major cloud providers by market share AWS, Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI) are compared across Intel, AMD, and ARM general purpose instance types under both on-demand and one-year discounted pricing. AWS consistently delivers the shortest runtime in all three instance types, yet charges a premium, especially for on-demand usage. OCI emerges as the most economical option across all CPU families, although it generally runs workloads more slowly than AWS. Azure often exhibits mid-range performance and cost, while GCP presents a mixed profile: it sees a notable boost when moving from Intel to AMD. On the other hand, its ARM instance is more than twice as slow as its own AMD offering and remains significantly more expensive. AWS's internal comparisons reveal that its ARM instance can outperform its Intel and AMD siblings by up to 49 percent in runtime. These findings highlight how instance choices and provider selection can yield substantial variations in both runtime and price, indicating that workload priorities, whether raw speed or cost minimization, should guide decisions on instance types.
Problem

Research questions and friction points this paper is trying to address.

Evaluating CPU performance and cost in cloud HPC workloads
Comparing four major cloud providers across different instance types
Analyzing trade-offs between runtime speed and pricing strategies
Innovation

Methods, ideas, or system contributions that make the work stand out.

Evaluated HPC CPU performance in cloud
Compared four providers across three architectures
Analyzed cost-performance tradeoffs for instance selection
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Jay Tharwani
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Shobhit Aggarwal
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Arnab A Purkayastha
Western New England University, Member IEEE, Springfield, MA, USA