Short answer: which one is better?

It depends on the workload and requirements. For continuous and predictable workloads, on-premises HPC generally offers lower TCO. For periodic and variable loads, cloud can be more flexible and economical.

Which option does Mevasis recommend?

The Mevasis expert team conducts a needs analysis and recommends the most suitable option. Rather than a one-size-fits-all answer, we provide an assessment tailored to your specific use case.

HPC vs Cloud: Which Is the Right Fit?

Q: What should I do to decide?

Contact us for a free technical assessment. Our team analyzes your workload profile, budget constraints, and security requirements to prepare a concrete recommendation.

HPC or Cloud? Asking the Right Question

High Performance Computing (HPC) and cloud computing are not competitors — they are two distinct approaches addressing different requirements. To make the right choice, it is first necessary to clarify what these two concepts mean.

On-premises HPC is the computing infrastructure that an organization builds in its own data center or colocation facility with physical servers, high-speed networking (such as InfiniBand), and parallel file systems (Lustre, GPFS). The organization owns the hardware; operations and capacity planning are the institution’s responsibility.

Cloud computing refers to virtual or physical compute resources offered on a rental basis by service providers such as AWS, Azure, and Google Cloud. Pay-as-you-go pricing, flexible scaling, and zero capital investment are key features. Today, major cloud providers also offer HPC-specific bare-metal cloud servers and InfiniBand-supported instances (AWS HPC6a, Azure HBv4 series).

There is no single correct answer when comparing these two approaches. The decision is shaped at the intersection of multiple factors: workload profile, budget structure, data privacy requirements, and organizational maturity level.

Comparison Table

Criterion	On-Premises HPC	Cloud Computing
Initial Cost (CapEx)	High — hardware, networking, data center infrastructure	Low — no server purchases
Long-Term TCO (3–5 years)	Generally lower for continuous workloads	Advantageous for variable loads; high OpEx for sustained use
Raw Compute Performance	Maximum — bare-metal, low latency, InfiniBand	Close but slightly lower — virtualization and shared network effects
Network Latency (MPI Workloads)	Sub-microsecond — InfiniBand HDR/NDR	A few microseconds — shared network environment
Scaling Flexibility	Limited — capacity increase requires hardware purchase	High — thousands of cores within minutes
Data Security and Compliance	Full control — data never leaves the facility	Provider-dependent; contract and compliance auditing required
Operational Burden	High — system administrators, hardware maintenance, software updates	Low — infrastructure managed by the provider
ISV Software Licensing	Perpetual or site licensing possible	Hourly licensing costs can quickly escalate
Data Transfer Cost	None — data stays on the local network	Egress charges can create significant costs for large datasets
Capacity Guarantee	Full — allocated resources always accessible	Variable — risk of instance exhaustion during peak periods

On-Premises HPC: Strengths

Performance superiority: Bare-metal access — with the virtualization layer removed — provides a clear advantage for MPI-based workloads. High-bandwidth, low-latency network fabrics like InfiniBand HDR or NDR make a critical difference in tightly coupled parallel applications (CFD, molecular dynamics, seismic modeling).

Predictable cost: Once hardware amortization is complete, operating cost largely consists of energy, cooling, and personnel. In continuous usage scenarios, this provides a significant TCO advantage over cloud.

Data sovereignty: For sensitive commercial data, defense projects, clinical research data, or workloads requiring national security, it is critically important that data does not leave the facility. On-premises architecture provides this control directly.

ISV licensing efficiency: Hourly cloud licenses for commercial simulation software like Fluent, MATLAB, or STAR-CCM+ can multiply the cost of perpetual licenses many times over under heavy usage.

On-Premises HPC: Weaknesses

High initial capital: Setting up a medium-scale HPC cluster can reach millions of dollars, including server and network hardware, storage, and data center improvements. This CapEx burden is subject to the institution’s budget cycle and capital planning process.

Lack of flexibility: When demand exceeds workload forecasts, capacity expansion takes weeks to months. With project-based or seasonal loads, this constraint translates to operational inefficiency.

Operational burden: Expert system management teams are required for hardware failures, software updates, security patches, and capacity planning. This indirect cost is often overlooked.

Cloud Computing: Strengths

Zero initial investment: No hardware purchase is needed at project start. This provides a fast launch opportunity for research projects, seasonal campaigns, or new business lines.

Near-unlimited scale: Thousands of cores or GPUs can be brought online within hours for sudden demands. In environments where peak loads are unpredictable, this flexibility creates value.

Managed services: With Kubernetes, Slurm on cloud, and fully managed workflow services, the system management burden decreases and teams can focus on their core work.

Geographic diversity: Computing distribution across multiple regions and disaster recovery scenarios can be easily configured.

Cloud Computing: Weaknesses

High sustaining cost: Under continuous usage, monthly cloud bills can significantly exceed the on-premises alternative over a 3–5 year perspective.

Data egress costs: For workloads working with large datasets, data transfer between regions or providers creates significant additional cost alongside compute costs.

Network latency: Tightly coupled parallel workloads can run slower than on-premises InfiniBand setups due to variability introduced by the shared network environment.

Provider dependency: Long-term contracts or platform-specific services increase migration costs in the future.

When to Use Which?

Choose On-Premises HPC:

Your workloads are continuous and predictable (16–24 hours of intensive use daily).
You run MPI-based tightly coupled simulations (CFD, structural analysis, seismic processing).
Data privacy or national security regulations prohibit data from leaving the facility.
ISV-licensed software is predominantly used and you want to benefit from perpetual licensing.
Total cost of ownership (TCO) over 3–5 years is the primary decision criterion.

Choose Cloud:

Workload demand shows seasonal, periodic, or sudden spikes.
Quick launch is a priority for a new project or research initiative.
System management capacity is limited; managed infrastructure advantage matters.
Data volume is relatively low and egress costs are calculable.
The workload is geographically distributed or requires multi-region collaboration.

Consider a Hybrid Approach:

Many large organizations operate an on-premises HPC cluster for core workloads while using cloud resources together for sudden demands (cloud bursting) or development/testing environments. This model can offer a balanced combination of performance and cost advantages, but requires proper architectural design and network integration.

The Right Step in Your Decision Process

The choice between HPC and cloud is not a one-time technical preference; it is a strategic decision that must be evaluated in conjunction with the organization’s growth trajectory, financial structure, and workload evolution.

At Mevasis, we offer a wide range of services from on-premises HPC design and installation to cloud HPC architecture, hybrid solutions, and managed operation models. We jointly analyze your workload profile, budget constraints, and security requirements to determine the most suitable approach for your needs.

Contact Mevasis for a free technical assessment. Our expert team prepares an evaluation report based on concrete data and a proposal specific to your use case.