CFD Cluster Background
CFD SOLUTION

Computational Fluid Dynamics Cluster

High-Performance Infrastructure for Simulation-Led Engineering

What is Computational Fluid Dynamics?

Computational Fluid Dynamics (CFD) is a high-performance computing workload used to model fluid flow, heat transfer, aerodynamics, and related multiphysics behaviour. Unlike conventional workloads, CFD relies on tightly coupled parallel processing across many CPU cores or nodes, demanding balanced compute, memory, networking, and storage infrastructure to deliver predictable performance.

Not Just “More Cores”

For engineering organisations, the objective is not simply to deploy more CPU cores, but to enable faster simulation turnaround time, and drive higher infrastructure considerations for designing CFD platforms, including compute, networking, storage, deployment models, and DiGiCOR's approach to delivering balanced HPC infrastructure.

Key Characteristics

Compute Intensive

Compute Intensive

In CFD simulations, the performance of the processor is critical to achieve results efficiently by handling complex numerical calculations and parallel processing.

Memory Bound

Memory Bound

CFD solution heavily depends on memory bandwidth and balanced memory population. The faster available memory is used across memory channels, the higher the processor and simulation performance will be.

Tightly Coupled Communication

Tightly Coupled Communication

CFD solvers efficiently exchange data between compute nodes, maximising low-latency networking performance essential for MPI performance.

Data Intensive Workflows

Data Intensive Workflows

CFD generates large volumes of mesh files, checkpoints, and simulation outputs that require scalable, high-performance storage.

Built around how CFD Workloads Actually Behaves

At DiGiCOR, compute nodes are selected according to workload profile and expected solver behaviour, not just core count. Memory is configured to sustain bandwidth and capacity requirements. Interconnect is sized to match cluster scale and communication intensity. Storage is designed to support active job data, checkpoints, results, and long-term retention without creating bottlenecks during execution.

CFD infrastructure should provide:

  • High compute performance
  • Balanced memory bandwidth
  • Low-latency networking
  • Scalable storage
  • Flexible deployment
CFD Workloads Behaviour

Designed for Real-World CFD Workload

Compute for CFD Throughput and Scalability

Modern CPU platforms have materially improved suitability for CFD and technical computing. Processor selection should be based on solver behaviour rather than core count alone. Memory bandwidth, cache capacity and NUMA configuration all contribute to simulation performance.

DiGiCOR optimises your infrastructure to offer high compute performance through:

  • Matching CPU architecture to solve behaviour
  • Balancing core and memory bandwidth
  • Populating all memory channels
  • Matching memory capacity to simulation size
  • Optimising BIOS and NUMA settings
  • Validating with representative workloads

Networking for Tightly Coupled Workloads

When CFD moves beyond a single workstation or server, networking becomes part of the solver path. Tightly coupled HPC workloads require constant communication between nodes, which is why low-latency, high-throughput fabrics are central to cluster design.

DiGiCOR designs cluster networking around workload scale and operating model, including:

  • Prioritising low latency networking for MPI workloads
  • Matching bandwidth to cluster size
  • Using RDMA where supported
  • Designing for balanced scalability

Storage for the CFD Data Lifecycle

CFD workflows generate more than solver demand. They also produce mesh data, checkpoints, transient outputs, and simulation results that must be written, accessed, and retained efficiently. Larger clusters therefore often require more capable shared storage approaches to avoid serialization and I/O bottlenecks.

DiGiCOR provides the infrastructure layer that supports CFD data lifecycle via:

  • Using high-performance storage for active jobs
  • Separating active an archive storage
  • Supporting shared team access
  • Scaling storage with simulation growth

Deployment Models

Different CFD environments have different operational requirements. DiGiCOR supports multiple deployments models to match workloads.

Bare metal servers

Bare Metal for Maximum Performance

For the most demanding distributed solver workloads, bare metal remains the most direct way to achieve predictable performance.

Virtualised HPC

Virtualised HPC Where Operational Flexibility Matters

Virtualised HPC is valuable when CFD is part of a broader engineering or enterprise environment. It provides stronger workload isolation, greater administrative flexibility, and easier infrastructure management while supporting shared enterprise resources.

Hyperconverged infrastructure

Hyperconverged Infrastructure for Selected Patterns

Hyperconverged infrastructure can also have a role in CFD-adjacent environments, especially for departmental deployments, mixed workloads, test and development, or environments where simplified operations are more important than extracting every last percentage point of distributed solver performance.

Featured Products

Storage

High-performance TrueNAS F-Series delivers the power and flexibility tailored for your CFD workload.

The TrueNAS F-Series delivers measurable impact across government, healthcare, service providers, media creation, higher education and other enterprises that demand high-performance storage for their critical data.

The TrueNAS F-Series can be used for:

  • Media Production: High-speed, scalable storage for video, audio, and VFX production workflows.
  • Analytics: High-performance, NVMe-powered storage designed to provide continuous accessibility and prevent data downtime.
  • Analytics: High-performance, NVMe-powered storage designed to provide continuous accessibility and prevent data downtime.
Explore TrueNAS F series
TrueNAS F-Series Storage Appliance

AMD EPYC Servers

Servers

Built on the AMD EPYC™ 9005 Series platform, two server models can be customised to fit your CFD workload.

AMD EPYC™ Rack Server can be used for:

  • Modern AI training
  • AI Inference
  • Visual Computing Deployments

Dual AMD EPYC™ PCIe Gen5 Rack Server can be used for:

  • Cloud-Native
  • Virtualisation
  • HPC
  • Technical Computing Workloads

Why Choose DiGiCOR?

Reliable Infrastructure

We deliver the infrastructure platform that underpins a CFD environment, including compute node design, storage architecture, networking, platform alignment, and integrated deployment.

Flexible Service

DiGiCOR’s portfolio explicitly spans servers, GPU systems, storage, networking, licensing/software, and end-to-end infrastructure services across design, build, deployment, migration, and support.

Customised Design

We ensure the infrastructure layer is robust, scalable, and properly matched to the workload so that the software environment is not constrained by the underlying platform. HPC specialists design computing, networking, and storage tiers tailored to your workload.

Explore HPC Environment

Assess Your CFD Readiness

Planning to deploy CFD infrastructure across your organisation?

  • Identify infrastructure, security, and governance gaps
  • Validate whether Bare Metal, Virtualised HPC or Hyperconverged model is right for your CFD workload
  • Design a secure and reliable CFD infrastructure aligned to your need
  • Built and supported locally by DiGiCOR

Computational Fluid Dynamics Readiness Checklist

Assess infrastructure, security, and governance readiness for CFD workload.

Let's Maximise Your Business Efficiency

Explore how DiGiCOR can utilise the power of CFD to manage your workload.

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