High Performance Computing

Heavy compute requires a different infrastructure.

Many organizations have moved beyond the AI experimentation phase. Models now need to run reliably in production, deliver real-time performance, and scale as demand grows. This requires GPU clusters and high-performance compute environments capable of handling intensive workloads, supported by an infrastructure designed to sustain that level of performance.

What is High Performance Computing?

High Performance Computing (HPC) is an environment where multiple powerful computer systems work together to perform complex calculations and process large volumes of data. Rather than relying on a single server, HPC uses clusters of interconnected systems, often equipped with specialized processors such as GPUs and high-speed storage, connected through low-latency networks capable of handling massive data flows.

These clusters place significant demands on the underlying infrastructure. They require abundant and reliable power, advanced cooling technologies beyond traditional data center environments, ultra-low-latency connectivity, and the flexibility to accommodate future hardware generations and growing capacity requirements.

HPC provides the proven foundation for AI-driven workloads such as:

• AI inferencing
• Real-time AI applications
• AI agents
• Data-intensive applicaitons
• Workloads with stringent latency and performance requirements

As a result, HPC requires more than compute power alone. The underlying data center environment must deliver sufficient power capacity, advanced cooling, low-latency connectivity, and resilient networking. Together, these elements determine whether AI workloads can run reliably, scale efficiently, and integrate seamlessly with the broader digital infrastructure.

The real bottleneck for AI is often the underlying infrastructure

In AI projects, the bottleneck is often not the software, but the underlying infrastructure. Power availability, cooling capacity, physical space, and connectivity can quickly become limiting factors, especially as workloads scale. Organizations need an environment that is readily available, can accommodate future hardware generations, and provides control over costs, performance, and data.

Eurofiber Groningen data center ready for compute-intensive workloads

Eurofiber operates a data center in Groningen that has been purpose-built for HPC environments and demanding AI workloads. Designed from the ground up to support high-density compute, it provides the power capacity, advanced cooling technologies, and low-latency connectivity required to run performance-intensive workloads at scale.

This enables:

• High power density per rack to support GPU servers and AI clusters
• Support for direct-to-chip and immersion cooling deployments
• Low-latency connectivity between data centers, cloud platforms, and end users
• Redundant power and network infrastructure

Groningen adds another advantage: room for growth, a strong digital infrastructure, and a mature innovation ecosystem. This makes it an attractive location for organizations looking to deploy HPC environments in a facility designed to scale with future compute demands, rather than one that has been retrofitted to accommodate them.

All of this is delivered from the Netherlands, under European regulations, providing greater control over where workloads run and how data is processed, stored, and connected.

Discover what HPC can do for your workloads.

Let's explore your AI workloads, compute requirements, growth ambitions, and the infrastructure needed to support them.

During the consultation, we will:

• Assess your current environment and requirements
• Evaluate latency, capacity, power, and connectivity needs
• Discuss how an HPC environment can integrate with your broader infrastructure
• Provide tailored advice on the infrastructure needed to support your AI and compute-intensive workloads