The ultimate guide to choosing the right computer for engineers

Complex simulations, data-intensive analytics, generative design, and digital twin technologies. They have become standard in the engineering world, and they all require serious computational power. Off-the-shelf PCs just don’t have what you need, and an underpowered system can compromise those tight project timelines, design accuracy, and ultimately, your competitive edge. 

Choosing the right engineering workstation puts vast amounts of processing power at your fingertips, an easy decision. Here’s what you need to know… 

The right workstation

When it comes to engineering workstations, it’s not a case of one size fits all. The optimal configuration is entirely dependent on your specific discipline, the scale of your projects, and your primary software applications. Are you a structural engineer performing Finite Elem Analysis? Or a mechanical engineer using CAD design? You need to be sure your workstation's capabilities are precisely matched to your engineering workflow.

4 Essential workstation components

very high-performance engineering workstation is built upon a foundation of four critical components, meticulously selected and optimized to deliver unparalleled stability and performance for your demanding projects:

• Multi-core processors (CPUs)

• High-end graphics cards or Graphics Processing Units (GPUs)

• Random Access Memory (RAM)

• Memory Storage (drive)

Engineering workstations

While engineering projects may rely on detailed visuals similar to design or architectural projects, graphic rendering capabilities may not be as important to you as the processing power needed to crunch large volumes of data. From intensive data processing, complex mathematical calculations, and large-scale simulations, you need to be sure your workstation can handle it all. 

Whether you’re running iterative, multi-physics simulations on vast datasets, training or deploying machine learning or AI model development, or perhaps processing massive geospatial data, you need a particular type of workflow and specific hardware. These differ from solutions that are simply optimised for graphic design. 

Interactive or computational workflow?

When choosing a computer for business, you should pick one that suits your workflow, depending on whether it’s interactive or computational. This distinction is paramount, as it directly dictates the optimal allocation of resources between your CPU and GPU, influencing overall system efficiency and performance.

Interactive workflow

Just as it sounds, interactive workflow describes a situation when highly responsive visuals are required, delivering fluid feedback from your software. This includes working with complex 3D models in CAD/CAM/CAE applications (e.g., SolidWorks, Autodesk Inventor, Revit, CATIA), navigating large assemblies, real-time visualization, and immersive virtual reality environments. 

You need a professional-grade GPU, such as NVIDIA RTX Ada Generation and high memory bandwidth to support smooth panning and real-time rendering. And while multi-core can be beneficial, you will be relying on your CPU’s per-core clock speed for responsiveness, so you want to ensure high clock-speeds under load. 

Computational workflow 

The workflow for computational projects, such as number crunching for analytical purposes, creating simulations and training a machine-learning model, is less graphics-intensive than visual design projects. Computational workflow is centred around processing vast datasets and executing complex algorithms. It can also be used for stress analysis, data analytics and rendering. For these kinds of workflow situations, CPUs with high core-counts are preferred over high clock-speed, so it’s best to choose a CPU with a high amount of on-chip memory. A large on-chip memory (L3 cache) further accelerates these operations by minimising data bottlenecks. And you should also consider multi-GPU configurations to leverage massive parallel processing power, as is needed with AI model training. 

Factors to consider

The financial investment for a top-of-the-range workstation gives pause for thought. Whatever the demands of your engineering projects, you’ll need all the hardware components listed below. However, you can reduce the overall cost by mixing and matching, depending on your requirements. The ability to upgrade at a later date should be a top consideration when deciding on your workstation components. 

Processing Power (CPU)

The brain of your engineering workstation, the CPU dictates how quickly your software can execute calculations and process data. Your choice of CPU core count and clock speed will heavily depend on whether your primary applications are more interactive or computational.

Graphics Processing Unit (GPU)

You need a powerful GPU or graphics card to render and visualise complex designs with 3D modelling and animation. But beyond rendering and visualising complex 3D models and animations in stunning detail, professional GPUs (such as NVIDIA RTX Ada Generation) are crucial for accelerating computationally intensive tasks through General Purpose GPU (GPGPU).

Storage drives

Big projects require terabytes of storage space in the form of drives to save project data. A primary NVMe Solid-State Drive (SSD) is essential for the operating system, applications, and active project files due to its unparalleled speed for boot times and load times. For secondary storage, larger SATA SSDs offer a good balance of capacity and speed for project archives and less frequently accessed data. 

Memory (RAM) 

Random Access Memory (RAM) is additional memory that’s used when work is in progress. For engineers, more RAM directly translates to the ability to load larger models, run more complex simulations, and switch between applications without slowdowns. While 32GB of DDR5 RAM might be an absolute minimum for basic CAD work, 64GB is now commonly recommended, with 128GB or even more becoming standard for heavy users of FEA, CFD, rendering, and data analysis.

Software compatibility

Perhaps the most critical factor when choosing a workstation, you need to ensure software compatibility and ISV certification. Basically, your hardware must not only meet the minimum requirements of your core engineering applications (e.g., MATLAB, CATIA, SolidWorks, Ansys, PTC Creo) but also be certified to run them optimally and reliably. 

Balance cost and performance

Choosing an engineering workstation is not simply a purchase, it is a long-term strategic investment. Rather than focusing on the up-front cost, you should be analysing return on investment and total cost of ownership to ensure value. A workstation that initially costs more but saves hundreds of hours in productivity, prevents costly project delays, and boasts a longer operational lifespan is far more economical in the long run.

Invest slightly more upfront for components that offer headroom for future projects and software updates, particularly in RAM, storage, and a robust motherboard for CPU/GPU upgrades. Ensure your workstation allows for easy component upgrades and protect your investment with comprehensive warranties. 

At NANUXPC we build workstations that truly accelerate your engineering potential

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